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You searched for subject:(statistical pattern recognition). Showing records 1 – 30 of 56 total matches.

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Rochester Institute of Technology

1. Kumar, Sriram. Learning Robust and Discriminative Manifold Representations for Pattern Recognition.

Degree: MS, Electrical Engineering, 2016, Rochester Institute of Technology

  Face and object recognition find applications in domains such as biometrics, surveillance and human computer interaction. An important component in any recognition pipeline is… (more)

Subjects/Keywords: Computer vision; Image processing; Machine learning; Pattern recognition; Statistical signal processing

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APA (6th Edition):

Kumar, S. (2016). Learning Robust and Discriminative Manifold Representations for Pattern Recognition. (Masters Thesis). Rochester Institute of Technology. Retrieved from https://scholarworks.rit.edu/theses/8983

Chicago Manual of Style (16th Edition):

Kumar, Sriram. “Learning Robust and Discriminative Manifold Representations for Pattern Recognition.” 2016. Masters Thesis, Rochester Institute of Technology. Accessed January 24, 2021. https://scholarworks.rit.edu/theses/8983.

MLA Handbook (7th Edition):

Kumar, Sriram. “Learning Robust and Discriminative Manifold Representations for Pattern Recognition.” 2016. Web. 24 Jan 2021.

Vancouver:

Kumar S. Learning Robust and Discriminative Manifold Representations for Pattern Recognition. [Internet] [Masters thesis]. Rochester Institute of Technology; 2016. [cited 2021 Jan 24]. Available from: https://scholarworks.rit.edu/theses/8983.

Council of Science Editors:

Kumar S. Learning Robust and Discriminative Manifold Representations for Pattern Recognition. [Masters Thesis]. Rochester Institute of Technology; 2016. Available from: https://scholarworks.rit.edu/theses/8983


Penn State University

2. Nazari, Saharnaz. IDENTIFYING BALLAST FOULING USING STATISTICAL PATTERN RECOGNITION TECHNIQUES ON SMARTROCK DATA.

Degree: 2018, Penn State University

 Railroad ballast serves different functions including draining water from track and distribution of the train loads. The ballast layer deteriorates and becomes fouled with time… (more)

Subjects/Keywords: Ballast Fouling; Railway; SmartRock; Statistical Pattern Recognition Analysis

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APA (6th Edition):

Nazari, S. (2018). IDENTIFYING BALLAST FOULING USING STATISTICAL PATTERN RECOGNITION TECHNIQUES ON SMARTROCK DATA. (Thesis). Penn State University. Retrieved from https://submit-etda.libraries.psu.edu/catalog/15244sun51

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Nazari, Saharnaz. “IDENTIFYING BALLAST FOULING USING STATISTICAL PATTERN RECOGNITION TECHNIQUES ON SMARTROCK DATA.” 2018. Thesis, Penn State University. Accessed January 24, 2021. https://submit-etda.libraries.psu.edu/catalog/15244sun51.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Nazari, Saharnaz. “IDENTIFYING BALLAST FOULING USING STATISTICAL PATTERN RECOGNITION TECHNIQUES ON SMARTROCK DATA.” 2018. Web. 24 Jan 2021.

Vancouver:

Nazari S. IDENTIFYING BALLAST FOULING USING STATISTICAL PATTERN RECOGNITION TECHNIQUES ON SMARTROCK DATA. [Internet] [Thesis]. Penn State University; 2018. [cited 2021 Jan 24]. Available from: https://submit-etda.libraries.psu.edu/catalog/15244sun51.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Nazari S. IDENTIFYING BALLAST FOULING USING STATISTICAL PATTERN RECOGNITION TECHNIQUES ON SMARTROCK DATA. [Thesis]. Penn State University; 2018. Available from: https://submit-etda.libraries.psu.edu/catalog/15244sun51

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


University of Texas – Austin

3. Morgan, Joseph Troy. Adaptive hierarchical classification with limited training data.

Degree: PhD, Mechanical Engineering., 2002, University of Texas – Austin

 This research focused on the development of a hierarchical approach for classification that is robust with respect to training data that are limited both in… (more)

Subjects/Keywords: Pattern recognition systems; Statistical decision

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APA (6th Edition):

Morgan, J. T. (2002). Adaptive hierarchical classification with limited training data. (Doctoral Dissertation). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/802

Chicago Manual of Style (16th Edition):

Morgan, Joseph Troy. “Adaptive hierarchical classification with limited training data.” 2002. Doctoral Dissertation, University of Texas – Austin. Accessed January 24, 2021. http://hdl.handle.net/2152/802.

MLA Handbook (7th Edition):

Morgan, Joseph Troy. “Adaptive hierarchical classification with limited training data.” 2002. Web. 24 Jan 2021.

Vancouver:

Morgan JT. Adaptive hierarchical classification with limited training data. [Internet] [Doctoral dissertation]. University of Texas – Austin; 2002. [cited 2021 Jan 24]. Available from: http://hdl.handle.net/2152/802.

Council of Science Editors:

Morgan JT. Adaptive hierarchical classification with limited training data. [Doctoral Dissertation]. University of Texas – Austin; 2002. Available from: http://hdl.handle.net/2152/802


Drexel University

4. Ford, Gabriel. Spectrum Awareness Using Bayesian Nonparametric Pattern Recognition.

Degree: 2018, Drexel University

To accommodate an increasing demand for scarce spectrum resources, dynamic spectrum access (DSA) opens portions of the spectrum currently dedicated to licensed primary users, for… (more)

Subjects/Keywords: Electrical engineering; Nonparametric signal detection; Bayesian statistical decision theory; Machine learning; Pattern recognition systems

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APA (6th Edition):

Ford, G. (2018). Spectrum Awareness Using Bayesian Nonparametric Pattern Recognition. (Thesis). Drexel University. Retrieved from https://idea.library.drexel.edu/islandora/object/idea%3A8177

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Ford, Gabriel. “Spectrum Awareness Using Bayesian Nonparametric Pattern Recognition.” 2018. Thesis, Drexel University. Accessed January 24, 2021. https://idea.library.drexel.edu/islandora/object/idea%3A8177.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Ford, Gabriel. “Spectrum Awareness Using Bayesian Nonparametric Pattern Recognition.” 2018. Web. 24 Jan 2021.

Vancouver:

Ford G. Spectrum Awareness Using Bayesian Nonparametric Pattern Recognition. [Internet] [Thesis]. Drexel University; 2018. [cited 2021 Jan 24]. Available from: https://idea.library.drexel.edu/islandora/object/idea%3A8177.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Ford G. Spectrum Awareness Using Bayesian Nonparametric Pattern Recognition. [Thesis]. Drexel University; 2018. Available from: https://idea.library.drexel.edu/islandora/object/idea%3A8177

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


Addis Ababa University

5. Ashenafi, Muluneh. Control Chart Pattern Recognition for Multivariate Autocorrelated Processes Using Artificial Neural Network .

Degree: 2014, Addis Ababa University

Statistical Process Control (SPC) is a powerful collection of problem-solving tools useful in achieving process stability and improving capability through the reduction of variability. Analysis… (more)

Subjects/Keywords: Multivariate Statistical Process control; Multivariate Autocorrelated Processes; Control Chart Pattern Recognition; Artificial Neural Network

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Ashenafi, M. (2014). Control Chart Pattern Recognition for Multivariate Autocorrelated Processes Using Artificial Neural Network . (Thesis). Addis Ababa University. Retrieved from http://etd.aau.edu.et/dspace/handle/123456789/5985

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Ashenafi, Muluneh. “Control Chart Pattern Recognition for Multivariate Autocorrelated Processes Using Artificial Neural Network .” 2014. Thesis, Addis Ababa University. Accessed January 24, 2021. http://etd.aau.edu.et/dspace/handle/123456789/5985.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Ashenafi, Muluneh. “Control Chart Pattern Recognition for Multivariate Autocorrelated Processes Using Artificial Neural Network .” 2014. Web. 24 Jan 2021.

Vancouver:

Ashenafi M. Control Chart Pattern Recognition for Multivariate Autocorrelated Processes Using Artificial Neural Network . [Internet] [Thesis]. Addis Ababa University; 2014. [cited 2021 Jan 24]. Available from: http://etd.aau.edu.et/dspace/handle/123456789/5985.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Ashenafi M. Control Chart Pattern Recognition for Multivariate Autocorrelated Processes Using Artificial Neural Network . [Thesis]. Addis Ababa University; 2014. Available from: http://etd.aau.edu.et/dspace/handle/123456789/5985

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


Freie Universität Berlin

6. Blume, Christian. Statistisches Lernen zur Modellierung von stratosphärischer Variabilität.

Degree: 2012, Freie Universität Berlin

 Die Variabilität der Stratosphäre ist entscheidend für die Entwicklung des gesamten Klimasystems. Stratosphärische Variabilität auf verschiedenen Zeitskalen wird beeinflusst durch eine Anzahl von Antrieben wie… (more)

Subjects/Keywords: Stratosphere; Pattern recognition; Statistical techniques; Time series; Forecasting; 500 Naturwissenschaften und Mathematik::550 Geowissenschaften, Geologie

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Blume, C. (2012). Statistisches Lernen zur Modellierung von stratosphärischer Variabilität. (Thesis). Freie Universität Berlin. Retrieved from https://refubium.fu-berlin.de/handle/fub188/13901

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Blume, Christian. “Statistisches Lernen zur Modellierung von stratosphärischer Variabilität.” 2012. Thesis, Freie Universität Berlin. Accessed January 24, 2021. https://refubium.fu-berlin.de/handle/fub188/13901.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Blume, Christian. “Statistisches Lernen zur Modellierung von stratosphärischer Variabilität.” 2012. Web. 24 Jan 2021.

Vancouver:

Blume C. Statistisches Lernen zur Modellierung von stratosphärischer Variabilität. [Internet] [Thesis]. Freie Universität Berlin; 2012. [cited 2021 Jan 24]. Available from: https://refubium.fu-berlin.de/handle/fub188/13901.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Blume C. Statistisches Lernen zur Modellierung von stratosphärischer Variabilität. [Thesis]. Freie Universität Berlin; 2012. Available from: https://refubium.fu-berlin.de/handle/fub188/13901

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


Univerzitet u Beogradu

7. Gajić, Dragoljub. Детекција епилептиформних активности у ЕЕГ сигналима применом статистичког препознавања облика.

Degree: Elektrotehnički fakultet, 2016, Univerzitet u Beogradu

Електротехника и рачунарство - Управљање системима и обрада сигнала / Electrical Engineering and Computer Science - Systems Control and Signal Processing

Епилепсија представља најучесталији поремећај… (more)

Subjects/Keywords: Epilepsy; Electroencephalogram; Epileptic Seizure; Seizure Detection; Seizure Prediction; Statistical Pattern Recognition; Wavelet Transform; Chaos Theory

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APA (6th Edition):

Gajić, D. (2016). Детекција епилептиформних активности у ЕЕГ сигналима применом статистичког препознавања облика. (Thesis). Univerzitet u Beogradu. Retrieved from https://fedorabg.bg.ac.rs/fedora/get/o:11880/bdef:Content/get

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Gajić, Dragoljub. “Детекција епилептиформних активности у ЕЕГ сигналима применом статистичког препознавања облика.” 2016. Thesis, Univerzitet u Beogradu. Accessed January 24, 2021. https://fedorabg.bg.ac.rs/fedora/get/o:11880/bdef:Content/get.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Gajić, Dragoljub. “Детекција епилептиформних активности у ЕЕГ сигналима применом статистичког препознавања облика.” 2016. Web. 24 Jan 2021.

Vancouver:

Gajić D. Детекција епилептиформних активности у ЕЕГ сигналима применом статистичког препознавања облика. [Internet] [Thesis]. Univerzitet u Beogradu; 2016. [cited 2021 Jan 24]. Available from: https://fedorabg.bg.ac.rs/fedora/get/o:11880/bdef:Content/get.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Gajić D. Детекција епилептиформних активности у ЕЕГ сигналима применом статистичког препознавања облика. [Thesis]. Univerzitet u Beogradu; 2016. Available from: https://fedorabg.bg.ac.rs/fedora/get/o:11880/bdef:Content/get

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


Columbia University

8. Yu, Gary. Identifying Patterns in Behavioral Public Health Data Using Mixture Modeling with an Informative Number of Repeated Measures.

Degree: 2014, Columbia University

 Finite mixture modeling is a useful statistical technique for clustering individuals based on patterns of responses. The fundamental idea of the mixture modeling approach is… (more)

Subjects/Keywords: Biometry; Public health – Research – Methodology; Cluster analysis; Pattern recognition systems – Statistical methods; Discriminant analysis; Machine learning – Statistical methods

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Yu, G. (2014). Identifying Patterns in Behavioral Public Health Data Using Mixture Modeling with an Informative Number of Repeated Measures. (Doctoral Dissertation). Columbia University. Retrieved from https://doi.org/10.7916/D8F197VX

Chicago Manual of Style (16th Edition):

Yu, Gary. “Identifying Patterns in Behavioral Public Health Data Using Mixture Modeling with an Informative Number of Repeated Measures.” 2014. Doctoral Dissertation, Columbia University. Accessed January 24, 2021. https://doi.org/10.7916/D8F197VX.

MLA Handbook (7th Edition):

Yu, Gary. “Identifying Patterns in Behavioral Public Health Data Using Mixture Modeling with an Informative Number of Repeated Measures.” 2014. Web. 24 Jan 2021.

Vancouver:

Yu G. Identifying Patterns in Behavioral Public Health Data Using Mixture Modeling with an Informative Number of Repeated Measures. [Internet] [Doctoral dissertation]. Columbia University; 2014. [cited 2021 Jan 24]. Available from: https://doi.org/10.7916/D8F197VX.

Council of Science Editors:

Yu G. Identifying Patterns in Behavioral Public Health Data Using Mixture Modeling with an Informative Number of Repeated Measures. [Doctoral Dissertation]. Columbia University; 2014. Available from: https://doi.org/10.7916/D8F197VX


RMIT University

9. Sun, L. REFORM: A framework for malware packer analysis using information theory and statistical methods.

Degree: 2010, RMIT University

 Malware (malicious software) is a term used to describe computer viruses, Trojan horses, and other pieces of software that are used to attack computer systems.… (more)

Subjects/Keywords: Fields of Research; malware; packer; packer analysis; packer classification; unpack; pattern recognition; information theory; statistical method

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APA (6th Edition):

Sun, L. (2010). REFORM: A framework for malware packer analysis using information theory and statistical methods. (Thesis). RMIT University. Retrieved from http://researchbank.rmit.edu.au/view/rmit:4934

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Sun, L. “REFORM: A framework for malware packer analysis using information theory and statistical methods.” 2010. Thesis, RMIT University. Accessed January 24, 2021. http://researchbank.rmit.edu.au/view/rmit:4934.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Sun, L. “REFORM: A framework for malware packer analysis using information theory and statistical methods.” 2010. Web. 24 Jan 2021.

Vancouver:

Sun L. REFORM: A framework for malware packer analysis using information theory and statistical methods. [Internet] [Thesis]. RMIT University; 2010. [cited 2021 Jan 24]. Available from: http://researchbank.rmit.edu.au/view/rmit:4934.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Sun L. REFORM: A framework for malware packer analysis using information theory and statistical methods. [Thesis]. RMIT University; 2010. Available from: http://researchbank.rmit.edu.au/view/rmit:4934

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

10. Silva Junior, Vilson Vieira da. Um estudo quantitativo sobre a evolução de movimentos artísticos.

Degree: Mestrado, Física Aplicada, 2014, University of São Paulo

Enquanto muitos estudos são feitos para a análise e classificação de pinturas e outros ramos das Artes, este estudo não se detém somente a classificação.… (more)

Subjects/Keywords: Arte; Arts; Barroco & arte moderna; Barroque & modern art; Física estatística; Painting; Pattern recognition; Pintura; Reconhecimento de padrões; Statistical physics

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APA (6th Edition):

Silva Junior, V. V. d. (2014). Um estudo quantitativo sobre a evolução de movimentos artísticos. (Masters Thesis). University of São Paulo. Retrieved from http://www.teses.usp.br/teses/disponiveis/76/76132/tde-22102014-074148/ ;

Chicago Manual of Style (16th Edition):

Silva Junior, Vilson Vieira da. “Um estudo quantitativo sobre a evolução de movimentos artísticos.” 2014. Masters Thesis, University of São Paulo. Accessed January 24, 2021. http://www.teses.usp.br/teses/disponiveis/76/76132/tde-22102014-074148/ ;.

MLA Handbook (7th Edition):

Silva Junior, Vilson Vieira da. “Um estudo quantitativo sobre a evolução de movimentos artísticos.” 2014. Web. 24 Jan 2021.

Vancouver:

Silva Junior VVd. Um estudo quantitativo sobre a evolução de movimentos artísticos. [Internet] [Masters thesis]. University of São Paulo; 2014. [cited 2021 Jan 24]. Available from: http://www.teses.usp.br/teses/disponiveis/76/76132/tde-22102014-074148/ ;.

Council of Science Editors:

Silva Junior VVd. Um estudo quantitativo sobre a evolução de movimentos artísticos. [Masters Thesis]. University of São Paulo; 2014. Available from: http://www.teses.usp.br/teses/disponiveis/76/76132/tde-22102014-074148/ ;


Vanderbilt University

11. Nik Hashim, Nik Nur Wahidah. Analysis of power spectrum density of male speech as indicators for high risk and depressed decision.

Degree: MS, Electrical Engineering, 2017, Vanderbilt University

 Assessment of a patients risk of committing suicide is important in order for them to be able to receive early hospitalization. The two critical mental… (more)

Subjects/Keywords: pattern recognition; classification; PSD; spectral energy; suicide; depression; statistical classification; suicidal speech; applied signal processing; resampling; speech

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Nik Hashim, N. N. W. (2017). Analysis of power spectrum density of male speech as indicators for high risk and depressed decision. (Thesis). Vanderbilt University. Retrieved from http://hdl.handle.net/1803/11286

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Nik Hashim, Nik Nur Wahidah. “Analysis of power spectrum density of male speech as indicators for high risk and depressed decision.” 2017. Thesis, Vanderbilt University. Accessed January 24, 2021. http://hdl.handle.net/1803/11286.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Nik Hashim, Nik Nur Wahidah. “Analysis of power spectrum density of male speech as indicators for high risk and depressed decision.” 2017. Web. 24 Jan 2021.

Vancouver:

Nik Hashim NNW. Analysis of power spectrum density of male speech as indicators for high risk and depressed decision. [Internet] [Thesis]. Vanderbilt University; 2017. [cited 2021 Jan 24]. Available from: http://hdl.handle.net/1803/11286.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Nik Hashim NNW. Analysis of power spectrum density of male speech as indicators for high risk and depressed decision. [Thesis]. Vanderbilt University; 2017. Available from: http://hdl.handle.net/1803/11286

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

12. Morrison, Paul. Shape matching based on skeletonisation and inexact graph matching.

Degree: 2011, Western Sydney University

 Shape matching is a difficult and important problem that remains unsolved. There are many applications of shape matching, including content-based image retrieval, computer-aided design, optical… (more)

Subjects/Keywords: Thesis (Ph.D.) – University of Western Sydney, 2011; pattern recognition systems; computer algorithms; image processing; digital techniques; statistical decision

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APA (6th Edition):

Morrison, P. (2011). Shape matching based on skeletonisation and inexact graph matching. (Thesis). Western Sydney University. Retrieved from http://handle.uws.edu.au:8081/1959.7/506687

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Morrison, Paul. “Shape matching based on skeletonisation and inexact graph matching.” 2011. Thesis, Western Sydney University. Accessed January 24, 2021. http://handle.uws.edu.au:8081/1959.7/506687.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Morrison, Paul. “Shape matching based on skeletonisation and inexact graph matching.” 2011. Web. 24 Jan 2021.

Vancouver:

Morrison P. Shape matching based on skeletonisation and inexact graph matching. [Internet] [Thesis]. Western Sydney University; 2011. [cited 2021 Jan 24]. Available from: http://handle.uws.edu.au:8081/1959.7/506687.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Morrison P. Shape matching based on skeletonisation and inexact graph matching. [Thesis]. Western Sydney University; 2011. Available from: http://handle.uws.edu.au:8081/1959.7/506687

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


University of Tennessee – Knoxville

13. Liu, Liu. Statistical Analysis of Disturbances in Power Transmission Systems.

Degree: MS, Computer Engineering, 2014, University of Tennessee – Knoxville

  Disturbance analysis is essential to the study of the power transmission systems. Traditionally, disturbances are described as megawatt (MW) events, but the access to… (more)

Subjects/Keywords: statistical analysis; distribution; disturbance; power system; pattern recognition; Other Computer Engineering; Power and Energy; Signal Processing

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APA (6th Edition):

Liu, L. (2014). Statistical Analysis of Disturbances in Power Transmission Systems. (Thesis). University of Tennessee – Knoxville. Retrieved from https://trace.tennessee.edu/utk_gradthes/2830

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Liu, Liu. “Statistical Analysis of Disturbances in Power Transmission Systems.” 2014. Thesis, University of Tennessee – Knoxville. Accessed January 24, 2021. https://trace.tennessee.edu/utk_gradthes/2830.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Liu, Liu. “Statistical Analysis of Disturbances in Power Transmission Systems.” 2014. Web. 24 Jan 2021.

Vancouver:

Liu L. Statistical Analysis of Disturbances in Power Transmission Systems. [Internet] [Thesis]. University of Tennessee – Knoxville; 2014. [cited 2021 Jan 24]. Available from: https://trace.tennessee.edu/utk_gradthes/2830.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Liu L. Statistical Analysis of Disturbances in Power Transmission Systems. [Thesis]. University of Tennessee – Knoxville; 2014. Available from: https://trace.tennessee.edu/utk_gradthes/2830

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

14. Dimartino, Michael. Statistical hand gesture recognition system using the Leap Motion Controller.

Degree: MS, Computer Science, 6, California State University – Northridge

 As technology continues to improve, hand gesture recognition as a form of human-computer interaction is becoming more and more feasible. One such piece of technology,… (more)

Subjects/Keywords: statistical pattern recognition; Dissertations, Academic  – CSUN  – Computer Science.

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APA (6th Edition):

Dimartino, M. (6). Statistical hand gesture recognition system using the Leap Motion Controller. (Masters Thesis). California State University – Northridge. Retrieved from http://hdl.handle.net/10211.3/171810

Chicago Manual of Style (16th Edition):

Dimartino, Michael. “Statistical hand gesture recognition system using the Leap Motion Controller.” 6. Masters Thesis, California State University – Northridge. Accessed January 24, 2021. http://hdl.handle.net/10211.3/171810.

MLA Handbook (7th Edition):

Dimartino, Michael. “Statistical hand gesture recognition system using the Leap Motion Controller.” 6. Web. 24 Jan 2021.

Vancouver:

Dimartino M. Statistical hand gesture recognition system using the Leap Motion Controller. [Internet] [Masters thesis]. California State University – Northridge; 6. [cited 2021 Jan 24]. Available from: http://hdl.handle.net/10211.3/171810.

Council of Science Editors:

Dimartino M. Statistical hand gesture recognition system using the Leap Motion Controller. [Masters Thesis]. California State University – Northridge; 6. Available from: http://hdl.handle.net/10211.3/171810

15. Lee, Andrea M. Prediction of High School Graduation with Decision Trees.

Degree: MSin Mathematics, Mathematics, 2019, Missouri State University

  While working as an educator for the past fourteen years, we are always looking at data and determining ways to help our students. Graduation… (more)

Subjects/Keywords: pattern recognition; supervised learning; decision trees; classification trees; nodes; target variable; pruning; graduation rate; proficiency; logistic regression; Statistical Theory

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APA (6th Edition):

Lee, A. M. (2019). Prediction of High School Graduation with Decision Trees. (Masters Thesis). Missouri State University. Retrieved from https://bearworks.missouristate.edu/theses/3419

Chicago Manual of Style (16th Edition):

Lee, Andrea M. “Prediction of High School Graduation with Decision Trees.” 2019. Masters Thesis, Missouri State University. Accessed January 24, 2021. https://bearworks.missouristate.edu/theses/3419.

MLA Handbook (7th Edition):

Lee, Andrea M. “Prediction of High School Graduation with Decision Trees.” 2019. Web. 24 Jan 2021.

Vancouver:

Lee AM. Prediction of High School Graduation with Decision Trees. [Internet] [Masters thesis]. Missouri State University; 2019. [cited 2021 Jan 24]. Available from: https://bearworks.missouristate.edu/theses/3419.

Council of Science Editors:

Lee AM. Prediction of High School Graduation with Decision Trees. [Masters Thesis]. Missouri State University; 2019. Available from: https://bearworks.missouristate.edu/theses/3419

16. Rudasi, Laszlo. Text-Independent Automatic Speaker Identification Using Partitioned Neural Networks.

Degree: PhD, Electrical/Computer Engineering, 1992, Old Dominion University

  This dissertation introduces a binary partitioned approach to statistical pattern classification which is applied to talker identification using neural networks. In recent years artificial… (more)

Subjects/Keywords: Pattern recognition; Neural networks; Statistical pattern classification; Computer Sciences; Electrical and Computer Engineering

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APA (6th Edition):

Rudasi, L. (1992). Text-Independent Automatic Speaker Identification Using Partitioned Neural Networks. (Doctoral Dissertation). Old Dominion University. Retrieved from https://digitalcommons.odu.edu/ece_etds/190

Chicago Manual of Style (16th Edition):

Rudasi, Laszlo. “Text-Independent Automatic Speaker Identification Using Partitioned Neural Networks.” 1992. Doctoral Dissertation, Old Dominion University. Accessed January 24, 2021. https://digitalcommons.odu.edu/ece_etds/190.

MLA Handbook (7th Edition):

Rudasi, Laszlo. “Text-Independent Automatic Speaker Identification Using Partitioned Neural Networks.” 1992. Web. 24 Jan 2021.

Vancouver:

Rudasi L. Text-Independent Automatic Speaker Identification Using Partitioned Neural Networks. [Internet] [Doctoral dissertation]. Old Dominion University; 1992. [cited 2021 Jan 24]. Available from: https://digitalcommons.odu.edu/ece_etds/190.

Council of Science Editors:

Rudasi L. Text-Independent Automatic Speaker Identification Using Partitioned Neural Networks. [Doctoral Dissertation]. Old Dominion University; 1992. Available from: https://digitalcommons.odu.edu/ece_etds/190


University of Florida

17. Roucos, Salim Estephan, 1954-. On small sample performance of pattern recognition machines.

Degree: 1980, University of Florida

Subjects/Keywords: Pattern recognition systems; Pattern perception; Statistical decision; Electrical Engineering thesis Ph. D; Pattern perception ( fast ); Pattern recognition systems ( fast ); Statistical decision ( fast )

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APA (6th Edition):

Roucos, Salim Estephan, 1. (1980). On small sample performance of pattern recognition machines. (Thesis). University of Florida. Retrieved from https://ufdc.ufl.edu/AA00068326

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Roucos, Salim Estephan, 1954-. “On small sample performance of pattern recognition machines.” 1980. Thesis, University of Florida. Accessed January 24, 2021. https://ufdc.ufl.edu/AA00068326.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Roucos, Salim Estephan, 1954-. “On small sample performance of pattern recognition machines.” 1980. Web. 24 Jan 2021.

Vancouver:

Roucos, Salim Estephan 1. On small sample performance of pattern recognition machines. [Internet] [Thesis]. University of Florida; 1980. [cited 2021 Jan 24]. Available from: https://ufdc.ufl.edu/AA00068326.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Roucos, Salim Estephan 1. On small sample performance of pattern recognition machines. [Thesis]. University of Florida; 1980. Available from: https://ufdc.ufl.edu/AA00068326

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

18. Francisco EstÃnio da Silva. Reconhecimento de PadrÃes AtravÃs de AnÃlises EstatÃsticas e Fractais Aplicadas a Dados de Ensaios NÃo-Destrutivos.

Degree: PhD, 2011, Universidade Federal do Ceará

 In this work a procedure is studied for pattern classification related to different types of data, namely: (1) signals obtained from ultrasonic testing ( pulse-echo… (more)

Subjects/Keywords: ENGENHARIA DE MATERIAIS E METALURGICA; Ensaios NÃo-Destrutivos; Soldagem; Nondestructive Testing; Statistical Fluctuations Analyses; Fractal Analyses; Statistical Pattern Recognition; Microstructural Changes Characterization; Welding Defects Classification

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Silva, F. E. d. (2011). Reconhecimento de PadrÃes AtravÃs de AnÃlises EstatÃsticas e Fractais Aplicadas a Dados de Ensaios NÃo-Destrutivos. (Doctoral Dissertation). Universidade Federal do Ceará. Retrieved from http://www.teses.ufc.br/tde_busca/arquivo.php?codArquivo=7330 ;

Chicago Manual of Style (16th Edition):

Silva, Francisco EstÃnio da. “Reconhecimento de PadrÃes AtravÃs de AnÃlises EstatÃsticas e Fractais Aplicadas a Dados de Ensaios NÃo-Destrutivos.” 2011. Doctoral Dissertation, Universidade Federal do Ceará. Accessed January 24, 2021. http://www.teses.ufc.br/tde_busca/arquivo.php?codArquivo=7330 ;.

MLA Handbook (7th Edition):

Silva, Francisco EstÃnio da. “Reconhecimento de PadrÃes AtravÃs de AnÃlises EstatÃsticas e Fractais Aplicadas a Dados de Ensaios NÃo-Destrutivos.” 2011. Web. 24 Jan 2021.

Vancouver:

Silva FEd. Reconhecimento de PadrÃes AtravÃs de AnÃlises EstatÃsticas e Fractais Aplicadas a Dados de Ensaios NÃo-Destrutivos. [Internet] [Doctoral dissertation]. Universidade Federal do Ceará 2011. [cited 2021 Jan 24]. Available from: http://www.teses.ufc.br/tde_busca/arquivo.php?codArquivo=7330 ;.

Council of Science Editors:

Silva FEd. Reconhecimento de PadrÃes AtravÃs de AnÃlises EstatÃsticas e Fractais Aplicadas a Dados de Ensaios NÃo-Destrutivos. [Doctoral Dissertation]. Universidade Federal do Ceará 2011. Available from: http://www.teses.ufc.br/tde_busca/arquivo.php?codArquivo=7330 ;


University of Oxford

19. Tsanas, Athanasios. Accurate telemonitoring of Parkinson's disease symptom severity using nonlinear speech signal processing and statistical machine learning.

Degree: PhD, 2012, University of Oxford

 This study focuses on the development of an objective, automated method to extract clinically useful information from sustained vowel phonations in the context of Parkinson’s… (more)

Subjects/Keywords: 616.833075; Biomedical engineering; Machine learning; Signal processing; Mathematical biology; Artificial Intelligence; Pattern recognition (statistics); Bioinformatics (technology); Mathematical modeling (engineering); Parkinson's disease; signal processing; statistical machine learning; pattern recognition; feature selection; Unified Parkinson's Disease Rating Scale (UPDRS)

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APA (6th Edition):

Tsanas, A. (2012). Accurate telemonitoring of Parkinson's disease symptom severity using nonlinear speech signal processing and statistical machine learning. (Doctoral Dissertation). University of Oxford. Retrieved from http://ora.ox.ac.uk/objects/uuid:2a43b92a-9cd5-4646-8f0f-81dbe2ba9d74 ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.572585

Chicago Manual of Style (16th Edition):

Tsanas, Athanasios. “Accurate telemonitoring of Parkinson's disease symptom severity using nonlinear speech signal processing and statistical machine learning.” 2012. Doctoral Dissertation, University of Oxford. Accessed January 24, 2021. http://ora.ox.ac.uk/objects/uuid:2a43b92a-9cd5-4646-8f0f-81dbe2ba9d74 ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.572585.

MLA Handbook (7th Edition):

Tsanas, Athanasios. “Accurate telemonitoring of Parkinson's disease symptom severity using nonlinear speech signal processing and statistical machine learning.” 2012. Web. 24 Jan 2021.

Vancouver:

Tsanas A. Accurate telemonitoring of Parkinson's disease symptom severity using nonlinear speech signal processing and statistical machine learning. [Internet] [Doctoral dissertation]. University of Oxford; 2012. [cited 2021 Jan 24]. Available from: http://ora.ox.ac.uk/objects/uuid:2a43b92a-9cd5-4646-8f0f-81dbe2ba9d74 ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.572585.

Council of Science Editors:

Tsanas A. Accurate telemonitoring of Parkinson's disease symptom severity using nonlinear speech signal processing and statistical machine learning. [Doctoral Dissertation]. University of Oxford; 2012. Available from: http://ora.ox.ac.uk/objects/uuid:2a43b92a-9cd5-4646-8f0f-81dbe2ba9d74 ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.572585

20. Cerqueira, Pedro Henrique Ramos. Um estudo sobre reconhecimento de padrões: um aprendizado supervisionado com classificador bayesiano.

Degree: Mestrado, Estatística e Experimentação Agronômica, 2011, University of São Paulo

A facilidade que temos para reconhecer um rosto, compreender palavras faladas, ler manuscritos, identicar chaves do carro no bolso e decidir se uma maçã está… (more)

Subjects/Keywords: Aprendizagem; Classication; Classificação; Estatística computacional; Inferência bayesiana; Learning; Marcador molecular; Mineração de dados; Molecular marker; Pattern Recognition; Probabilidade; Reconhecimento de padrões; Softwares.; Statistical nnnnadaaaaacomputing.

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APA (6th Edition):

Cerqueira, P. H. R. (2011). Um estudo sobre reconhecimento de padrões: um aprendizado supervisionado com classificador bayesiano. (Masters Thesis). University of São Paulo. Retrieved from http://www.teses.usp.br/teses/disponiveis/11/11134/tde-11022011-101732/ ;

Chicago Manual of Style (16th Edition):

Cerqueira, Pedro Henrique Ramos. “Um estudo sobre reconhecimento de padrões: um aprendizado supervisionado com classificador bayesiano.” 2011. Masters Thesis, University of São Paulo. Accessed January 24, 2021. http://www.teses.usp.br/teses/disponiveis/11/11134/tde-11022011-101732/ ;.

MLA Handbook (7th Edition):

Cerqueira, Pedro Henrique Ramos. “Um estudo sobre reconhecimento de padrões: um aprendizado supervisionado com classificador bayesiano.” 2011. Web. 24 Jan 2021.

Vancouver:

Cerqueira PHR. Um estudo sobre reconhecimento de padrões: um aprendizado supervisionado com classificador bayesiano. [Internet] [Masters thesis]. University of São Paulo; 2011. [cited 2021 Jan 24]. Available from: http://www.teses.usp.br/teses/disponiveis/11/11134/tde-11022011-101732/ ;.

Council of Science Editors:

Cerqueira PHR. Um estudo sobre reconhecimento de padrões: um aprendizado supervisionado com classificador bayesiano. [Masters Thesis]. University of São Paulo; 2011. Available from: http://www.teses.usp.br/teses/disponiveis/11/11134/tde-11022011-101732/ ;

21. Morard, Vincent. Détection de structures fines par traitement d'images et apprentissage statistique : application au contrôle non destructif : Thin structures detection by means of image processing and statistical learning : application to non-destructive testing.

Degree: Docteur es, Morphologie mathématique, 2012, Paris, ENMP

Dans cette thèse, nous présentons de nouvelles méthodes de traitement d’images pourextraire ou rehausser les éléments fins d’une image. Pour ces opérateurs, issus de la… (more)

Subjects/Keywords: Traitement d'images; Morphologie Mathématique; Analyse statistique; Caractérisation de formes; Contrôles non destructifs; Ouvertures parcimonieuses par chemins; Image processing; Mathematical morphology; Statistical analysis; Pattern recognition; Non destructive testing; Parsimonious path openings

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Morard, V. (2012). Détection de structures fines par traitement d'images et apprentissage statistique : application au contrôle non destructif : Thin structures detection by means of image processing and statistical learning : application to non-destructive testing. (Doctoral Dissertation). Paris, ENMP. Retrieved from http://www.theses.fr/2012ENMP0101

Chicago Manual of Style (16th Edition):

Morard, Vincent. “Détection de structures fines par traitement d'images et apprentissage statistique : application au contrôle non destructif : Thin structures detection by means of image processing and statistical learning : application to non-destructive testing.” 2012. Doctoral Dissertation, Paris, ENMP. Accessed January 24, 2021. http://www.theses.fr/2012ENMP0101.

MLA Handbook (7th Edition):

Morard, Vincent. “Détection de structures fines par traitement d'images et apprentissage statistique : application au contrôle non destructif : Thin structures detection by means of image processing and statistical learning : application to non-destructive testing.” 2012. Web. 24 Jan 2021.

Vancouver:

Morard V. Détection de structures fines par traitement d'images et apprentissage statistique : application au contrôle non destructif : Thin structures detection by means of image processing and statistical learning : application to non-destructive testing. [Internet] [Doctoral dissertation]. Paris, ENMP; 2012. [cited 2021 Jan 24]. Available from: http://www.theses.fr/2012ENMP0101.

Council of Science Editors:

Morard V. Détection de structures fines par traitement d'images et apprentissage statistique : application au contrôle non destructif : Thin structures detection by means of image processing and statistical learning : application to non-destructive testing. [Doctoral Dissertation]. Paris, ENMP; 2012. Available from: http://www.theses.fr/2012ENMP0101


University of Michigan

22. Morris, Milton Mayo. Design of statistical pattern recognition methods for improved cardiac rhythm specificity by implantable cardioverter defibrillators.

Degree: PhD, Electrical engineering, 1997, University of Michigan

 Sudden cardiac death (SCD) claims the lives of over 400,000 people annually. A modern medical device called the implantable cardioverter defibrillator (ICD) is used to… (more)

Subjects/Keywords: Cardiac; Cardioverter; Defibrillators; Design; Implantable; Improved; Methods; Pattern; Recognition; Rhythm; Specificity; Statistical

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APA (6th Edition):

Morris, M. M. (1997). Design of statistical pattern recognition methods for improved cardiac rhythm specificity by implantable cardioverter defibrillators. (Doctoral Dissertation). University of Michigan. Retrieved from http://hdl.handle.net/2027.42/130310

Chicago Manual of Style (16th Edition):

Morris, Milton Mayo. “Design of statistical pattern recognition methods for improved cardiac rhythm specificity by implantable cardioverter defibrillators.” 1997. Doctoral Dissertation, University of Michigan. Accessed January 24, 2021. http://hdl.handle.net/2027.42/130310.

MLA Handbook (7th Edition):

Morris, Milton Mayo. “Design of statistical pattern recognition methods for improved cardiac rhythm specificity by implantable cardioverter defibrillators.” 1997. Web. 24 Jan 2021.

Vancouver:

Morris MM. Design of statistical pattern recognition methods for improved cardiac rhythm specificity by implantable cardioverter defibrillators. [Internet] [Doctoral dissertation]. University of Michigan; 1997. [cited 2021 Jan 24]. Available from: http://hdl.handle.net/2027.42/130310.

Council of Science Editors:

Morris MM. Design of statistical pattern recognition methods for improved cardiac rhythm specificity by implantable cardioverter defibrillators. [Doctoral Dissertation]. University of Michigan; 1997. Available from: http://hdl.handle.net/2027.42/130310


Vanderbilt University

23. Wan Ahmad Sanadi, Wan Ahmad Hasan. Acoustic analysis of speech based on power spectral density features in detecting suicidal risk among female patients.

Degree: MS, Electrical Engineering, 2011, Vanderbilt University

 Suicide is a major public health problem in the US. The procedure to measure the degree of suicidal risk in depressed patients is complicated and… (more)

Subjects/Keywords: Pattern recognition; Suicide symptoms; Machine learning; Applied signal processing; Speech processing; Suicidal speech; Spectral energy; Suicidal behavior; Depressive speech; Depression symptoms; Statistical classification; Depression behavior

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APA (6th Edition):

Wan Ahmad Sanadi, W. A. H. (2011). Acoustic analysis of speech based on power spectral density features in detecting suicidal risk among female patients. (Thesis). Vanderbilt University. Retrieved from http://hdl.handle.net/1803/11287

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Wan Ahmad Sanadi, Wan Ahmad Hasan. “Acoustic analysis of speech based on power spectral density features in detecting suicidal risk among female patients.” 2011. Thesis, Vanderbilt University. Accessed January 24, 2021. http://hdl.handle.net/1803/11287.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Wan Ahmad Sanadi, Wan Ahmad Hasan. “Acoustic analysis of speech based on power spectral density features in detecting suicidal risk among female patients.” 2011. Web. 24 Jan 2021.

Vancouver:

Wan Ahmad Sanadi WAH. Acoustic analysis of speech based on power spectral density features in detecting suicidal risk among female patients. [Internet] [Thesis]. Vanderbilt University; 2011. [cited 2021 Jan 24]. Available from: http://hdl.handle.net/1803/11287.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Wan Ahmad Sanadi WAH. Acoustic analysis of speech based on power spectral density features in detecting suicidal risk among female patients. [Thesis]. Vanderbilt University; 2011. Available from: http://hdl.handle.net/1803/11287

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

24. Li, Na. MMD and Ward criterion in a RKHS : application to Kernel based hierarchical agglomerative clustering : Maximum Dean Discrepancy et critère de Ward dans un RKHS : application à la classification hierarchique à noyau.

Degree: Docteur es, Optimisation et Sûreté des Systèmes, 2015, Troyes

La classification non supervisée consiste à regrouper des objets afin de former des groupes homogènes au sens d’une mesure de similitude. C’est un outil utile… (more)

Subjects/Keywords: Classification automatique (statistique); Reconnaissance des formes (informatique); Apprentissage automatique; Tests d'hypothèses (statistique); Cluster analysis; Pattern recognition systems; Machine learning; Statistical hypothesis testing; 620.004 52

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APA (6th Edition):

Li, N. (2015). MMD and Ward criterion in a RKHS : application to Kernel based hierarchical agglomerative clustering : Maximum Dean Discrepancy et critère de Ward dans un RKHS : application à la classification hierarchique à noyau. (Doctoral Dissertation). Troyes. Retrieved from http://www.theses.fr/2015TROY0033

Chicago Manual of Style (16th Edition):

Li, Na. “MMD and Ward criterion in a RKHS : application to Kernel based hierarchical agglomerative clustering : Maximum Dean Discrepancy et critère de Ward dans un RKHS : application à la classification hierarchique à noyau.” 2015. Doctoral Dissertation, Troyes. Accessed January 24, 2021. http://www.theses.fr/2015TROY0033.

MLA Handbook (7th Edition):

Li, Na. “MMD and Ward criterion in a RKHS : application to Kernel based hierarchical agglomerative clustering : Maximum Dean Discrepancy et critère de Ward dans un RKHS : application à la classification hierarchique à noyau.” 2015. Web. 24 Jan 2021.

Vancouver:

Li N. MMD and Ward criterion in a RKHS : application to Kernel based hierarchical agglomerative clustering : Maximum Dean Discrepancy et critère de Ward dans un RKHS : application à la classification hierarchique à noyau. [Internet] [Doctoral dissertation]. Troyes; 2015. [cited 2021 Jan 24]. Available from: http://www.theses.fr/2015TROY0033.

Council of Science Editors:

Li N. MMD and Ward criterion in a RKHS : application to Kernel based hierarchical agglomerative clustering : Maximum Dean Discrepancy et critère de Ward dans un RKHS : application à la classification hierarchique à noyau. [Doctoral Dissertation]. Troyes; 2015. Available from: http://www.theses.fr/2015TROY0033

25. Pereira, João Tiago Martins Neves. Applicability of the statistical pattern recognition paradigm for structural health monitoring of bridges.

Degree: 2012, RCAAP

In the last decades, health monitoring systems have gained an increasing importance in our society. The main purpose of these systems is to support the… (more)

Subjects/Keywords: Damage Detection; Bridge Failures; Statistical Pattern Recognition Paradigm; Structural Health Monitoring; Deteção de Dano; Desastres de Pontes; Paradigma de Reconhecimento de Padrões; Monitorização da Integridade Estrutural

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APA (6th Edition):

Pereira, J. T. M. N. (2012). Applicability of the statistical pattern recognition paradigm for structural health monitoring of bridges. (Thesis). RCAAP. Retrieved from http://www.rcaap.pt/detail.jsp?id=oai:repositorio.ucp.pt:10400.14/15656

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Pereira, João Tiago Martins Neves. “Applicability of the statistical pattern recognition paradigm for structural health monitoring of bridges.” 2012. Thesis, RCAAP. Accessed January 24, 2021. http://www.rcaap.pt/detail.jsp?id=oai:repositorio.ucp.pt:10400.14/15656.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Pereira, João Tiago Martins Neves. “Applicability of the statistical pattern recognition paradigm for structural health monitoring of bridges.” 2012. Web. 24 Jan 2021.

Vancouver:

Pereira JTMN. Applicability of the statistical pattern recognition paradigm for structural health monitoring of bridges. [Internet] [Thesis]. RCAAP; 2012. [cited 2021 Jan 24]. Available from: http://www.rcaap.pt/detail.jsp?id=oai:repositorio.ucp.pt:10400.14/15656.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Pereira JTMN. Applicability of the statistical pattern recognition paradigm for structural health monitoring of bridges. [Thesis]. RCAAP; 2012. Available from: http://www.rcaap.pt/detail.jsp?id=oai:repositorio.ucp.pt:10400.14/15656

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


The Ohio State University

26. Zhu, Manli. A study of the generalized eigenvalue decomposition in discriminant analysis.

Degree: PhD, Electrical Engineering, 2006, The Ohio State University

  The well-known Linear Discriminant Analysis (LDA) approach to feature extraction in classification problems is typically formulated using a generalized eigenvalue decomposition, S 1V=S 2VΛ,… (more)

Subjects/Keywords: statistical pattern recognition; classification; feature extraction; discriminant analysis; microarray; bioinformatics

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APA (6th Edition):

Zhu, M. (2006). A study of the generalized eigenvalue decomposition in discriminant analysis. (Doctoral Dissertation). The Ohio State University. Retrieved from http://rave.ohiolink.edu/etdc/view?acc_num=osu1152133627

Chicago Manual of Style (16th Edition):

Zhu, Manli. “A study of the generalized eigenvalue decomposition in discriminant analysis.” 2006. Doctoral Dissertation, The Ohio State University. Accessed January 24, 2021. http://rave.ohiolink.edu/etdc/view?acc_num=osu1152133627.

MLA Handbook (7th Edition):

Zhu, Manli. “A study of the generalized eigenvalue decomposition in discriminant analysis.” 2006. Web. 24 Jan 2021.

Vancouver:

Zhu M. A study of the generalized eigenvalue decomposition in discriminant analysis. [Internet] [Doctoral dissertation]. The Ohio State University; 2006. [cited 2021 Jan 24]. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=osu1152133627.

Council of Science Editors:

Zhu M. A study of the generalized eigenvalue decomposition in discriminant analysis. [Doctoral Dissertation]. The Ohio State University; 2006. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=osu1152133627


Georgia Tech

27. Fu, Qiang. A generalization of the minimum classification error (MCE) training method for speech recognition and detection.

Degree: PhD, Electrical and Computer Engineering, 2008, Georgia Tech

 The model training algorithm is a critical component in the statistical pattern recognition approaches which are based on the Bayes decision theory. Conventional applications of… (more)

Subjects/Keywords: MVE; P-MCE; Non-uniform error cost; Automatic speech recognition; Bayesian statistical decision theory; Pattern recognition systems

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Fu, Q. (2008). A generalization of the minimum classification error (MCE) training method for speech recognition and detection. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/22705

Chicago Manual of Style (16th Edition):

Fu, Qiang. “A generalization of the minimum classification error (MCE) training method for speech recognition and detection.” 2008. Doctoral Dissertation, Georgia Tech. Accessed January 24, 2021. http://hdl.handle.net/1853/22705.

MLA Handbook (7th Edition):

Fu, Qiang. “A generalization of the minimum classification error (MCE) training method for speech recognition and detection.” 2008. Web. 24 Jan 2021.

Vancouver:

Fu Q. A generalization of the minimum classification error (MCE) training method for speech recognition and detection. [Internet] [Doctoral dissertation]. Georgia Tech; 2008. [cited 2021 Jan 24]. Available from: http://hdl.handle.net/1853/22705.

Council of Science Editors:

Fu Q. A generalization of the minimum classification error (MCE) training method for speech recognition and detection. [Doctoral Dissertation]. Georgia Tech; 2008. Available from: http://hdl.handle.net/1853/22705


Georgia Tech

28. Yaman, Sibel. A multi-objective programming perspective to statistical learning problems.

Degree: PhD, Electrical and Computer Engineering, 2008, Georgia Tech

 It has been increasingly recognized that realistic problems often involve a tradeoff among many conflicting objectives. Traditional methods aim at satisfying multiple objectives by combining… (more)

Subjects/Keywords: Pattern recognition; Statistical language modeling; Automatic speech recognition; Multiobjective optimization; Speech processing systems; Electronic data processing; Interpolation; Approximation theory

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Yaman, S. (2008). A multi-objective programming perspective to statistical learning problems. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/26470

Chicago Manual of Style (16th Edition):

Yaman, Sibel. “A multi-objective programming perspective to statistical learning problems.” 2008. Doctoral Dissertation, Georgia Tech. Accessed January 24, 2021. http://hdl.handle.net/1853/26470.

MLA Handbook (7th Edition):

Yaman, Sibel. “A multi-objective programming perspective to statistical learning problems.” 2008. Web. 24 Jan 2021.

Vancouver:

Yaman S. A multi-objective programming perspective to statistical learning problems. [Internet] [Doctoral dissertation]. Georgia Tech; 2008. [cited 2021 Jan 24]. Available from: http://hdl.handle.net/1853/26470.

Council of Science Editors:

Yaman S. A multi-objective programming perspective to statistical learning problems. [Doctoral Dissertation]. Georgia Tech; 2008. Available from: http://hdl.handle.net/1853/26470


IUPUI

29. Ghane, Parisa. Silent speech recognition in EEG-based brain computer interface.

Degree: 2015, IUPUI

Indiana University-Purdue University Indianapolis (IUPUI)

A Brain Computer Interface (BCI) is a hardware and software system that establishes direct communication between human brain and the… (more)

Subjects/Keywords: Brain Computer Interface; EEG; Support Vector Machine; Multi-class Classification; Speech recognition; Brain-computer interfaces  – Research  – Analysis; Electroencephalography  – Mathematical models; Support vector machines  – Research  – Analysis; Speech processing systems  – Research; Automatic speech recognition  – Research  – Analysis; Pattern recognition systems  – Statistical methods; Multimedia systems  – Research; Neural networks (Computer science)  – Research; Wavelets (Mathematics); Computer algorithms  – Research; User interfaces (Computer systems); Electrodes  – Testing

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Ghane, P. (2015). Silent speech recognition in EEG-based brain computer interface. (Thesis). IUPUI. Retrieved from http://hdl.handle.net/1805/9886

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Ghane, Parisa. “Silent speech recognition in EEG-based brain computer interface.” 2015. Thesis, IUPUI. Accessed January 24, 2021. http://hdl.handle.net/1805/9886.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Ghane, Parisa. “Silent speech recognition in EEG-based brain computer interface.” 2015. Web. 24 Jan 2021.

Vancouver:

Ghane P. Silent speech recognition in EEG-based brain computer interface. [Internet] [Thesis]. IUPUI; 2015. [cited 2021 Jan 24]. Available from: http://hdl.handle.net/1805/9886.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Ghane P. Silent speech recognition in EEG-based brain computer interface. [Thesis]. IUPUI; 2015. Available from: http://hdl.handle.net/1805/9886

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


University of Oulu

30. Vuollo, V. (Ville). 3D imaging and nonparametric function estimation methods for analysis of infant cranial shape and detection of twin zygosity.

Degree: 2018, University of Oulu

Abstract The use of 3D imaging of craniofacial soft tissue has increased in medical science, and imaging technology has been developed greatly in recent years.… (more)

Subjects/Keywords: 3D surface imaging; cranial deformations; directional statistics; head shape; kernel density estimation; scale space; spherical data; statistical pattern recognition; stereophotogrammetry; twin study; zygosity; 3D-kuvantaminen; epämuotoisuus; kaksostutkimus; pallopinnan data; pään muoto; skaala-avaruus; stereofotogrammetria; tilastollinen hahmontunnistus; tsygositeetti; ydinestimointi

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Vuollo, V. (. (2018). 3D imaging and nonparametric function estimation methods for analysis of infant cranial shape and detection of twin zygosity. (Doctoral Dissertation). University of Oulu. Retrieved from http://urn.fi/urn:isbn:9789526218557

Chicago Manual of Style (16th Edition):

Vuollo, V (Ville). “3D imaging and nonparametric function estimation methods for analysis of infant cranial shape and detection of twin zygosity.” 2018. Doctoral Dissertation, University of Oulu. Accessed January 24, 2021. http://urn.fi/urn:isbn:9789526218557.

MLA Handbook (7th Edition):

Vuollo, V (Ville). “3D imaging and nonparametric function estimation methods for analysis of infant cranial shape and detection of twin zygosity.” 2018. Web. 24 Jan 2021.

Vancouver:

Vuollo V(. 3D imaging and nonparametric function estimation methods for analysis of infant cranial shape and detection of twin zygosity. [Internet] [Doctoral dissertation]. University of Oulu; 2018. [cited 2021 Jan 24]. Available from: http://urn.fi/urn:isbn:9789526218557.

Council of Science Editors:

Vuollo V(. 3D imaging and nonparametric function estimation methods for analysis of infant cranial shape and detection of twin zygosity. [Doctoral Dissertation]. University of Oulu; 2018. Available from: http://urn.fi/urn:isbn:9789526218557

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