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You searched for subject:(Pattern Recognition). Showing records 1 – 30 of 1824 total matches.

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University of KwaZulu-Natal

1. Schuld, Maria. Quantum machine learning for supervised pattern recognition.: How quantum computers learn from data.

Degree: 2017, University of KwaZulu-Natal

 Humans are experts at recognising patterns in past experience and applying them to new tasks. For example, after seeing pictures of a face we can… (more)

Subjects/Keywords: Pattern.; Recognition.

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

APA (6th Edition):

Schuld, M. (2017). Quantum machine learning for supervised pattern recognition.: How quantum computers learn from data. (Thesis). University of KwaZulu-Natal. Retrieved from http://hdl.handle.net/10413/15748

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):

Schuld, Maria. “Quantum machine learning for supervised pattern recognition.: How quantum computers learn from data.” 2017. Thesis, University of KwaZulu-Natal. Accessed May 26, 2019. http://hdl.handle.net/10413/15748.

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

MLA Handbook (7th Edition):

Schuld, Maria. “Quantum machine learning for supervised pattern recognition.: How quantum computers learn from data.” 2017. Web. 26 May 2019.

Vancouver:

Schuld M. Quantum machine learning for supervised pattern recognition.: How quantum computers learn from data. [Internet] [Thesis]. University of KwaZulu-Natal; 2017. [cited 2019 May 26]. Available from: http://hdl.handle.net/10413/15748.

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

Council of Science Editors:

Schuld M. Quantum machine learning for supervised pattern recognition.: How quantum computers learn from data. [Thesis]. University of KwaZulu-Natal; 2017. Available from: http://hdl.handle.net/10413/15748

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


Queens University

2. Seniuk, Andrew G. Pen-Chant : Acoustic Emissions of Handwriting and Drawing .

Degree: Computing, 2009, Queens University

 The sounds generated by a writing instrument ("pen-chant") provide a rich and under-utilized source of information for pattern recognition. We examine the feasibility of recognition(more)

Subjects/Keywords: Pattern Recognition; Handwriting Recognition

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APA (6th Edition):

Seniuk, A. G. (2009). Pen-Chant : Acoustic Emissions of Handwriting and Drawing . (Thesis). Queens University. Retrieved from http://hdl.handle.net/1974/5236

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):

Seniuk, Andrew G. “Pen-Chant : Acoustic Emissions of Handwriting and Drawing .” 2009. Thesis, Queens University. Accessed May 26, 2019. http://hdl.handle.net/1974/5236.

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

MLA Handbook (7th Edition):

Seniuk, Andrew G. “Pen-Chant : Acoustic Emissions of Handwriting and Drawing .” 2009. Web. 26 May 2019.

Vancouver:

Seniuk AG. Pen-Chant : Acoustic Emissions of Handwriting and Drawing . [Internet] [Thesis]. Queens University; 2009. [cited 2019 May 26]. Available from: http://hdl.handle.net/1974/5236.

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

Council of Science Editors:

Seniuk AG. Pen-Chant : Acoustic Emissions of Handwriting and Drawing . [Thesis]. Queens University; 2009. Available from: http://hdl.handle.net/1974/5236

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


De Montfort University

3. Al Rifaee, Mustafa Moh'd Husien. Unconstrained iris recognition.

Degree: PhD, 2014, De Montfort University

 This research focuses on iris recognition, the most accurate form of biometric identification. The robustness of iris recognition comes from the unique characteristics of the… (more)

Subjects/Keywords: 600; Pattern Recognition

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APA (6th Edition):

Al Rifaee, M. M. H. (2014). Unconstrained iris recognition. (Doctoral Dissertation). De Montfort University. Retrieved from http://hdl.handle.net/2086/10949

Chicago Manual of Style (16th Edition):

Al Rifaee, Mustafa Moh'd Husien. “Unconstrained iris recognition.” 2014. Doctoral Dissertation, De Montfort University. Accessed May 26, 2019. http://hdl.handle.net/2086/10949.

MLA Handbook (7th Edition):

Al Rifaee, Mustafa Moh'd Husien. “Unconstrained iris recognition.” 2014. Web. 26 May 2019.

Vancouver:

Al Rifaee MMH. Unconstrained iris recognition. [Internet] [Doctoral dissertation]. De Montfort University; 2014. [cited 2019 May 26]. Available from: http://hdl.handle.net/2086/10949.

Council of Science Editors:

Al Rifaee MMH. Unconstrained iris recognition. [Doctoral Dissertation]. De Montfort University; 2014. Available from: http://hdl.handle.net/2086/10949


University of Hong Kong

4. Ni, Zhibo. Artificial training samples for the improvement of pattern recognitionsystems.

Degree: PhD, 2012, University of Hong Kong

Pattern recognition is the assignment of some sort of label to a given input value or instance, according to some specific learning algorithm. The recognition(more)

Subjects/Keywords: Pattern recognition systems.

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APA (6th Edition):

Ni, Z. (2012). Artificial training samples for the improvement of pattern recognitionsystems. (Doctoral Dissertation). University of Hong Kong. Retrieved from Ni, Z. [倪志博]. (2012). Artificial training samples for the improvement of pattern recognition systems. (Thesis). University of Hong Kong, Pokfulam, Hong Kong SAR. Retrieved from http://dx.doi.org/10.5353/th_b4784964 ; http://dx.doi.org/10.5353/th_b4784964 ; http://hdl.handle.net/10722/174522

Chicago Manual of Style (16th Edition):

Ni, Zhibo. “Artificial training samples for the improvement of pattern recognitionsystems.” 2012. Doctoral Dissertation, University of Hong Kong. Accessed May 26, 2019. Ni, Z. [倪志博]. (2012). Artificial training samples for the improvement of pattern recognition systems. (Thesis). University of Hong Kong, Pokfulam, Hong Kong SAR. Retrieved from http://dx.doi.org/10.5353/th_b4784964 ; http://dx.doi.org/10.5353/th_b4784964 ; http://hdl.handle.net/10722/174522.

MLA Handbook (7th Edition):

Ni, Zhibo. “Artificial training samples for the improvement of pattern recognitionsystems.” 2012. Web. 26 May 2019.

Vancouver:

Ni Z. Artificial training samples for the improvement of pattern recognitionsystems. [Internet] [Doctoral dissertation]. University of Hong Kong; 2012. [cited 2019 May 26]. Available from: Ni, Z. [倪志博]. (2012). Artificial training samples for the improvement of pattern recognition systems. (Thesis). University of Hong Kong, Pokfulam, Hong Kong SAR. Retrieved from http://dx.doi.org/10.5353/th_b4784964 ; http://dx.doi.org/10.5353/th_b4784964 ; http://hdl.handle.net/10722/174522.

Council of Science Editors:

Ni Z. Artificial training samples for the improvement of pattern recognitionsystems. [Doctoral Dissertation]. University of Hong Kong; 2012. Available from: Ni, Z. [倪志博]. (2012). Artificial training samples for the improvement of pattern recognition systems. (Thesis). University of Hong Kong, Pokfulam, Hong Kong SAR. Retrieved from http://dx.doi.org/10.5353/th_b4784964 ; http://dx.doi.org/10.5353/th_b4784964 ; http://hdl.handle.net/10722/174522


Hong Kong University of Science and Technology

5. Xiao, Xiangye. Efficient co-location pattern discovery.

Degree: 2009, Hong Kong University of Science and Technology

 Co-location pattern discovery is to find classes of objects whose associated spatial locations are frequently in proximity. For example, map search queries, which contain keywords… (more)

Subjects/Keywords: Pattern recognition systems

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APA (6th Edition):

Xiao, X. (2009). Efficient co-location pattern discovery. (Thesis). Hong Kong University of Science and Technology. Retrieved from https://doi.org/10.14711/thesis-b1070780 ; http://repository.ust.hk/ir/bitstream/1783.1-6349/1/th_redirect.html

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):

Xiao, Xiangye. “Efficient co-location pattern discovery.” 2009. Thesis, Hong Kong University of Science and Technology. Accessed May 26, 2019. https://doi.org/10.14711/thesis-b1070780 ; http://repository.ust.hk/ir/bitstream/1783.1-6349/1/th_redirect.html.

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

MLA Handbook (7th Edition):

Xiao, Xiangye. “Efficient co-location pattern discovery.” 2009. Web. 26 May 2019.

Vancouver:

Xiao X. Efficient co-location pattern discovery. [Internet] [Thesis]. Hong Kong University of Science and Technology; 2009. [cited 2019 May 26]. Available from: https://doi.org/10.14711/thesis-b1070780 ; http://repository.ust.hk/ir/bitstream/1783.1-6349/1/th_redirect.html.

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

Council of Science Editors:

Xiao X. Efficient co-location pattern discovery. [Thesis]. Hong Kong University of Science and Technology; 2009. Available from: https://doi.org/10.14711/thesis-b1070780 ; http://repository.ust.hk/ir/bitstream/1783.1-6349/1/th_redirect.html

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

6. Karunakara, K. Some contributions to the study of pattern recognition;.

Degree: Computer science and engineering, 2014, Kuvempu University

Abstract available newline

Advisors/Committee Members: Mallikarjunaswamy, B P.

Subjects/Keywords: Pattern recognition

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APA (6th Edition):

Karunakara, K. (2014). Some contributions to the study of pattern recognition;. (Thesis). Kuvempu University. Retrieved from http://shodhganga.inflibnet.ac.in/handle/10603/25143

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):

Karunakara, K. “Some contributions to the study of pattern recognition;.” 2014. Thesis, Kuvempu University. Accessed May 26, 2019. http://shodhganga.inflibnet.ac.in/handle/10603/25143.

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

MLA Handbook (7th Edition):

Karunakara, K. “Some contributions to the study of pattern recognition;.” 2014. Web. 26 May 2019.

Vancouver:

Karunakara K. Some contributions to the study of pattern recognition;. [Internet] [Thesis]. Kuvempu University; 2014. [cited 2019 May 26]. Available from: http://shodhganga.inflibnet.ac.in/handle/10603/25143.

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

Council of Science Editors:

Karunakara K. Some contributions to the study of pattern recognition;. [Thesis]. Kuvempu University; 2014. Available from: http://shodhganga.inflibnet.ac.in/handle/10603/25143

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


Loughborough University

7. Adam, Mohamad Z. Unfamiliar facial identity registration and recognition performance enhancement.

Degree: 2013, Loughborough University

 The work in this thesis aims at studying the problems related to the robustness of a face recognition system where specific attention is given to… (more)

Subjects/Keywords: Pattern recognition; Image understanding

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APA (6th Edition):

Adam, M. Z. (2013). Unfamiliar facial identity registration and recognition performance enhancement. (Doctoral Dissertation). Loughborough University. Retrieved from https://dspace.lboro.ac.uk/2134/11431 ; http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.564390

Chicago Manual of Style (16th Edition):

Adam, Mohamad Z. “Unfamiliar facial identity registration and recognition performance enhancement.” 2013. Doctoral Dissertation, Loughborough University. Accessed May 26, 2019. https://dspace.lboro.ac.uk/2134/11431 ; http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.564390.

MLA Handbook (7th Edition):

Adam, Mohamad Z. “Unfamiliar facial identity registration and recognition performance enhancement.” 2013. Web. 26 May 2019.

Vancouver:

Adam MZ. Unfamiliar facial identity registration and recognition performance enhancement. [Internet] [Doctoral dissertation]. Loughborough University; 2013. [cited 2019 May 26]. Available from: https://dspace.lboro.ac.uk/2134/11431 ; http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.564390.

Council of Science Editors:

Adam MZ. Unfamiliar facial identity registration and recognition performance enhancement. [Doctoral Dissertation]. Loughborough University; 2013. Available from: https://dspace.lboro.ac.uk/2134/11431 ; http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.564390


NSYSU

8. Chen, Po-ju. A Bometric Verification method based on Knee Accerlation Signal.

Degree: Master, Mechanical and Electro-Mechanical Engineering, 2008, NSYSU

 Abstract With the rapid progress of the MEMs process, the cost and the size of accelerometers are reducing rapidly. As a result, accelerometers have found… (more)

Subjects/Keywords: acceleration; VQ; hypersphere; pattern recognition

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APA (6th Edition):

Chen, P. (2008). A Bometric Verification method based on Knee Accerlation Signal. (Thesis). NSYSU. Retrieved from http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0721108-160528

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):

Chen, Po-ju. “A Bometric Verification method based on Knee Accerlation Signal.” 2008. Thesis, NSYSU. Accessed May 26, 2019. http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0721108-160528.

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

MLA Handbook (7th Edition):

Chen, Po-ju. “A Bometric Verification method based on Knee Accerlation Signal.” 2008. Web. 26 May 2019.

Vancouver:

Chen P. A Bometric Verification method based on Knee Accerlation Signal. [Internet] [Thesis]. NSYSU; 2008. [cited 2019 May 26]. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0721108-160528.

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

Council of Science Editors:

Chen P. A Bometric Verification method based on Knee Accerlation Signal. [Thesis]. NSYSU; 2008. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0721108-160528

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


University of Hawaii – Manoa

9. Chêng, Tsê. Automatic labeling, modeling and recognition for line-drawing interpretation.

Degree: PhD, 2009, University of Hawaii – Manoa

Microfiche.

xvi, 191 leaves, bound ill. 29 cm

With the advent of the information era, line-drawing with digital form has become increasingly important in engineering… (more)

Subjects/Keywords: Computer graphics; Optical pattern recognition

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APA (6th Edition):

Chêng, T. (2009). Automatic labeling, modeling and recognition for line-drawing interpretation. (Doctoral Dissertation). University of Hawaii – Manoa. Retrieved from http://hdl.handle.net/10125/9750

Chicago Manual of Style (16th Edition):

Chêng, Tsê. “Automatic labeling, modeling and recognition for line-drawing interpretation.” 2009. Doctoral Dissertation, University of Hawaii – Manoa. Accessed May 26, 2019. http://hdl.handle.net/10125/9750.

MLA Handbook (7th Edition):

Chêng, Tsê. “Automatic labeling, modeling and recognition for line-drawing interpretation.” 2009. Web. 26 May 2019.

Vancouver:

Chêng T. Automatic labeling, modeling and recognition for line-drawing interpretation. [Internet] [Doctoral dissertation]. University of Hawaii – Manoa; 2009. [cited 2019 May 26]. Available from: http://hdl.handle.net/10125/9750.

Council of Science Editors:

Chêng T. Automatic labeling, modeling and recognition for line-drawing interpretation. [Doctoral Dissertation]. University of Hawaii – Manoa; 2009. Available from: http://hdl.handle.net/10125/9750


Penn State University

10. Lidstone, Stephanie Ann. Modeling and Analysis of Complex Manufacturing Systems – Application of Data Visualization and Pattern Recognition Techniques.

Degree: MS, Industrial Engineering, 2012, Penn State University

 Complex manufacturing systems can be challenging to analyze and improve. The intricate nature of these systems makes it difficult to anticipate how modifications in one… (more)

Subjects/Keywords: data visualization; manufacturing; pattern recognition

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APA (6th Edition):

Lidstone, S. A. (2012). Modeling and Analysis of Complex Manufacturing Systems – Application of Data Visualization and Pattern Recognition Techniques. (Masters Thesis). Penn State University. Retrieved from https://etda.libraries.psu.edu/catalog/13827

Chicago Manual of Style (16th Edition):

Lidstone, Stephanie Ann. “Modeling and Analysis of Complex Manufacturing Systems – Application of Data Visualization and Pattern Recognition Techniques.” 2012. Masters Thesis, Penn State University. Accessed May 26, 2019. https://etda.libraries.psu.edu/catalog/13827.

MLA Handbook (7th Edition):

Lidstone, Stephanie Ann. “Modeling and Analysis of Complex Manufacturing Systems – Application of Data Visualization and Pattern Recognition Techniques.” 2012. Web. 26 May 2019.

Vancouver:

Lidstone SA. Modeling and Analysis of Complex Manufacturing Systems – Application of Data Visualization and Pattern Recognition Techniques. [Internet] [Masters thesis]. Penn State University; 2012. [cited 2019 May 26]. Available from: https://etda.libraries.psu.edu/catalog/13827.

Council of Science Editors:

Lidstone SA. Modeling and Analysis of Complex Manufacturing Systems – Application of Data Visualization and Pattern Recognition Techniques. [Masters Thesis]. Penn State University; 2012. Available from: https://etda.libraries.psu.edu/catalog/13827


University of Saskatchewan

11. Yu, Zexi 1989-. Co-Segmentation Methods for Improving Tumor Target Delineation in PET-CT Images.

Degree: 2016, University of Saskatchewan

 Positron emission tomography (PET)-Computed tomography (CT) plays an important role in cancer management. As a multi-modal imaging technique it provides both functional and anatomical information… (more)

Subjects/Keywords: Pattern Recognition; Medical Image Processing

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APA (6th Edition):

Yu, Z. 1. (2016). Co-Segmentation Methods for Improving Tumor Target Delineation in PET-CT Images. (Thesis). University of Saskatchewan. Retrieved from http://hdl.handle.net/10388/7624

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):

Yu, Zexi 1989-. “Co-Segmentation Methods for Improving Tumor Target Delineation in PET-CT Images.” 2016. Thesis, University of Saskatchewan. Accessed May 26, 2019. http://hdl.handle.net/10388/7624.

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

MLA Handbook (7th Edition):

Yu, Zexi 1989-. “Co-Segmentation Methods for Improving Tumor Target Delineation in PET-CT Images.” 2016. Web. 26 May 2019.

Vancouver:

Yu Z1. Co-Segmentation Methods for Improving Tumor Target Delineation in PET-CT Images. [Internet] [Thesis]. University of Saskatchewan; 2016. [cited 2019 May 26]. Available from: http://hdl.handle.net/10388/7624.

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

Council of Science Editors:

Yu Z1. Co-Segmentation Methods for Improving Tumor Target Delineation in PET-CT Images. [Thesis]. University of Saskatchewan; 2016. Available from: http://hdl.handle.net/10388/7624

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

12. Karim, Ehsanul; Madani, Sri Phani Venkata Siva Krishna. Fuzzy Clustering Analysis.

Degree: 2010, , School of Engineering

  The Objective of this thesis is to talk about the usage of Fuzzy Logic in pattern recognition. There are different fuzzy approaches to recognize… (more)

Subjects/Keywords: Fuzzy Clustering; Pattern Recognition

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APA (6th Edition):

Karim, Ehsanul; Madani, S. P. V. S. K. (2010). Fuzzy Clustering Analysis. (Thesis). , School of Engineering. Retrieved from http://urn.kb.se/resolve?urn=urn:nbn:se:bth-2165

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):

Karim, Ehsanul; Madani, Sri Phani Venkata Siva Krishna. “Fuzzy Clustering Analysis.” 2010. Thesis, , School of Engineering. Accessed May 26, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-2165.

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

MLA Handbook (7th Edition):

Karim, Ehsanul; Madani, Sri Phani Venkata Siva Krishna. “Fuzzy Clustering Analysis.” 2010. Web. 26 May 2019.

Vancouver:

Karim, Ehsanul; Madani SPVSK. Fuzzy Clustering Analysis. [Internet] [Thesis]. , School of Engineering; 2010. [cited 2019 May 26]. Available from: http://urn.kb.se/resolve?urn=urn:nbn:se:bth-2165.

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

Council of Science Editors:

Karim, Ehsanul; Madani SPVSK. Fuzzy Clustering Analysis. [Thesis]. , School of Engineering; 2010. Available from: http://urn.kb.se/resolve?urn=urn:nbn:se:bth-2165

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


Delft University of Technology

13. Hoogenboezem, R.M. Automatic classification of segmented seismic recordings at the Nevado del Ruiz volcano, Columbia:.

Degree: 2010, Delft University of Technology

 The Nevado del Ruiz volcano is an active and dangerous volcano in the Andean volcanic belt. Measuring seismic activity is one of the most reliable… (more)

Subjects/Keywords: pattern recognition; seismic recordings

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APA (6th Edition):

Hoogenboezem, R. M. (2010). Automatic classification of segmented seismic recordings at the Nevado del Ruiz volcano, Columbia:. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:5de9543b-cda8-4397-b61a-4e5f17639dff

Chicago Manual of Style (16th Edition):

Hoogenboezem, R M. “Automatic classification of segmented seismic recordings at the Nevado del Ruiz volcano, Columbia:.” 2010. Masters Thesis, Delft University of Technology. Accessed May 26, 2019. http://resolver.tudelft.nl/uuid:5de9543b-cda8-4397-b61a-4e5f17639dff.

MLA Handbook (7th Edition):

Hoogenboezem, R M. “Automatic classification of segmented seismic recordings at the Nevado del Ruiz volcano, Columbia:.” 2010. Web. 26 May 2019.

Vancouver:

Hoogenboezem RM. Automatic classification of segmented seismic recordings at the Nevado del Ruiz volcano, Columbia:. [Internet] [Masters thesis]. Delft University of Technology; 2010. [cited 2019 May 26]. Available from: http://resolver.tudelft.nl/uuid:5de9543b-cda8-4397-b61a-4e5f17639dff.

Council of Science Editors:

Hoogenboezem RM. Automatic classification of segmented seismic recordings at the Nevado del Ruiz volcano, Columbia:. [Masters Thesis]. Delft University of Technology; 2010. Available from: http://resolver.tudelft.nl/uuid:5de9543b-cda8-4397-b61a-4e5f17639dff


Delft University of Technology

14. Karavides, T. Database guided detection of anatomical landmark points in 3D images of the heart:.

Degree: 2009, Delft University of Technology

 Automated landmark detection may prove important for the examination and automatic analysis of real-time three-dimensional (3D) echocardiograms. By detecting 3D anatomical landmark points, the standard… (more)

Subjects/Keywords: classification; pattern recognition; ultrasound

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APA (6th Edition):

Karavides, T. (2009). Database guided detection of anatomical landmark points in 3D images of the heart:. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:17e80d25-36d0-41c5-8a18-f5e7a6976a1b

Chicago Manual of Style (16th Edition):

Karavides, T. “Database guided detection of anatomical landmark points in 3D images of the heart:.” 2009. Masters Thesis, Delft University of Technology. Accessed May 26, 2019. http://resolver.tudelft.nl/uuid:17e80d25-36d0-41c5-8a18-f5e7a6976a1b.

MLA Handbook (7th Edition):

Karavides, T. “Database guided detection of anatomical landmark points in 3D images of the heart:.” 2009. Web. 26 May 2019.

Vancouver:

Karavides T. Database guided detection of anatomical landmark points in 3D images of the heart:. [Internet] [Masters thesis]. Delft University of Technology; 2009. [cited 2019 May 26]. Available from: http://resolver.tudelft.nl/uuid:17e80d25-36d0-41c5-8a18-f5e7a6976a1b.

Council of Science Editors:

Karavides T. Database guided detection of anatomical landmark points in 3D images of the heart:. [Masters Thesis]. Delft University of Technology; 2009. Available from: http://resolver.tudelft.nl/uuid:17e80d25-36d0-41c5-8a18-f5e7a6976a1b


University of Cape Town

15. Goss, Ryan Gavin. APIC: A method for automated pattern identification and classification.

Degree: Image, Computer Science, 2017, University of Cape Town

 Machine Learning (ML) is a transformative technology at the forefront of many modern research endeavours. The technology is generating a tremendous amount of attention from… (more)

Subjects/Keywords: Pattern Recognition; Machine Learning

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

APA (6th Edition):

Goss, R. G. (2017). APIC: A method for automated pattern identification and classification. (Thesis). University of Cape Town. Retrieved from http://hdl.handle.net/11427/27025

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):

Goss, Ryan Gavin. “APIC: A method for automated pattern identification and classification.” 2017. Thesis, University of Cape Town. Accessed May 26, 2019. http://hdl.handle.net/11427/27025.

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

MLA Handbook (7th Edition):

Goss, Ryan Gavin. “APIC: A method for automated pattern identification and classification.” 2017. Web. 26 May 2019.

Vancouver:

Goss RG. APIC: A method for automated pattern identification and classification. [Internet] [Thesis]. University of Cape Town; 2017. [cited 2019 May 26]. Available from: http://hdl.handle.net/11427/27025.

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

Council of Science Editors:

Goss RG. APIC: A method for automated pattern identification and classification. [Thesis]. University of Cape Town; 2017. Available from: http://hdl.handle.net/11427/27025

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


University of New South Wales

16. Xi, Kai. Biometric Security System Design: From Mobile to Cloud Computing Environment.

Degree: Engineering & Information Technology Canberra, 2012, University of New South Wales

 Worldwide adoption of mobile products and cloud computing services not only continues, but is accelerating. Biometric security technology shows promising in addressing the issue of… (more)

Subjects/Keywords: Pattern recognition; Biometrics; Information security

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

APA (6th Edition):

Xi, K. (2012). Biometric Security System Design: From Mobile to Cloud Computing Environment. (Doctoral Dissertation). University of New South Wales. Retrieved from http://handle.unsw.edu.au/1959.4/52179 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:10849/SOURCE01?view=true

Chicago Manual of Style (16th Edition):

Xi, Kai. “Biometric Security System Design: From Mobile to Cloud Computing Environment.” 2012. Doctoral Dissertation, University of New South Wales. Accessed May 26, 2019. http://handle.unsw.edu.au/1959.4/52179 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:10849/SOURCE01?view=true.

MLA Handbook (7th Edition):

Xi, Kai. “Biometric Security System Design: From Mobile to Cloud Computing Environment.” 2012. Web. 26 May 2019.

Vancouver:

Xi K. Biometric Security System Design: From Mobile to Cloud Computing Environment. [Internet] [Doctoral dissertation]. University of New South Wales; 2012. [cited 2019 May 26]. Available from: http://handle.unsw.edu.au/1959.4/52179 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:10849/SOURCE01?view=true.

Council of Science Editors:

Xi K. Biometric Security System Design: From Mobile to Cloud Computing Environment. [Doctoral Dissertation]. University of New South Wales; 2012. Available from: http://handle.unsw.edu.au/1959.4/52179 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:10849/SOURCE01?view=true


University of Newcastle

17. Miller, Peter. Pattern recognition is a clinical reasoning process in musculoskeletal physiotherapy.

Degree: 2009, University of Newcastle

Masters Research - Master of Medical Science

Pattern recognition is a non-analytical clinical reasoning process which has been reported in the medical and allied health… (more)

Subjects/Keywords: pattern recognition; clinical reasoning; physiotherapy

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

APA (6th Edition):

Miller, P. (2009). Pattern recognition is a clinical reasoning process in musculoskeletal physiotherapy. (Thesis). University of Newcastle. Retrieved from http://hdl.handle.net/1959.13/44629

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):

Miller, Peter. “Pattern recognition is a clinical reasoning process in musculoskeletal physiotherapy.” 2009. Thesis, University of Newcastle. Accessed May 26, 2019. http://hdl.handle.net/1959.13/44629.

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

MLA Handbook (7th Edition):

Miller, Peter. “Pattern recognition is a clinical reasoning process in musculoskeletal physiotherapy.” 2009. Web. 26 May 2019.

Vancouver:

Miller P. Pattern recognition is a clinical reasoning process in musculoskeletal physiotherapy. [Internet] [Thesis]. University of Newcastle; 2009. [cited 2019 May 26]. Available from: http://hdl.handle.net/1959.13/44629.

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

Council of Science Editors:

Miller P. Pattern recognition is a clinical reasoning process in musculoskeletal physiotherapy. [Thesis]. University of Newcastle; 2009. Available from: http://hdl.handle.net/1959.13/44629

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


University of Notre Dame

18. Rachel Elizabeth Kasuboski-Polando. The role of pattern recognition receptors in host cell signaling and phagosome maturation during infection with Leishmania</h1>.

Degree: PhD, Biological Sciences, 2009, University of Notre Dame

  Leishmaniasis is a devastating group of diseases causing substantial mortality and morbidity throughout the world. Leishmania are obligate intracellular organisms infecting and replicating inside… (more)

Subjects/Keywords: Leishmania; Macrophage; pattern recognition

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APA (6th Edition):

Kasuboski-Polando, R. E. (2009). The role of pattern recognition receptors in host cell signaling and phagosome maturation during infection with Leishmania</h1>. (Doctoral Dissertation). University of Notre Dame. Retrieved from https://curate.nd.edu/show/x059c536z9s

Chicago Manual of Style (16th Edition):

Kasuboski-Polando, Rachel Elizabeth. “The role of pattern recognition receptors in host cell signaling and phagosome maturation during infection with Leishmania</h1>.” 2009. Doctoral Dissertation, University of Notre Dame. Accessed May 26, 2019. https://curate.nd.edu/show/x059c536z9s.

MLA Handbook (7th Edition):

Kasuboski-Polando, Rachel Elizabeth. “The role of pattern recognition receptors in host cell signaling and phagosome maturation during infection with Leishmania</h1>.” 2009. Web. 26 May 2019.

Vancouver:

Kasuboski-Polando RE. The role of pattern recognition receptors in host cell signaling and phagosome maturation during infection with Leishmania</h1>. [Internet] [Doctoral dissertation]. University of Notre Dame; 2009. [cited 2019 May 26]. Available from: https://curate.nd.edu/show/x059c536z9s.

Council of Science Editors:

Kasuboski-Polando RE. The role of pattern recognition receptors in host cell signaling and phagosome maturation during infection with Leishmania</h1>. [Doctoral Dissertation]. University of Notre Dame; 2009. Available from: https://curate.nd.edu/show/x059c536z9s


Oregon State University

19. Zhang, Wei. Image features and learning algorithms for biological, generic and social object recognition.

Degree: PhD, Electrical and Computer Engineering, 2009, Oregon State University

 Automated recognition of object categories in images is a critical step for many real-world computer vision applications. Interest region detectors and region descriptors have been… (more)

Subjects/Keywords: object recognition; Optical pattern recognition  – Mathematical models

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

APA (6th Edition):

Zhang, W. (2009). Image features and learning algorithms for biological, generic and social object recognition. (Doctoral Dissertation). Oregon State University. Retrieved from http://hdl.handle.net/1957/11178

Chicago Manual of Style (16th Edition):

Zhang, Wei. “Image features and learning algorithms for biological, generic and social object recognition.” 2009. Doctoral Dissertation, Oregon State University. Accessed May 26, 2019. http://hdl.handle.net/1957/11178.

MLA Handbook (7th Edition):

Zhang, Wei. “Image features and learning algorithms for biological, generic and social object recognition.” 2009. Web. 26 May 2019.

Vancouver:

Zhang W. Image features and learning algorithms for biological, generic and social object recognition. [Internet] [Doctoral dissertation]. Oregon State University; 2009. [cited 2019 May 26]. Available from: http://hdl.handle.net/1957/11178.

Council of Science Editors:

Zhang W. Image features and learning algorithms for biological, generic and social object recognition. [Doctoral Dissertation]. Oregon State University; 2009. Available from: http://hdl.handle.net/1957/11178


Virginia Tech

20. Saha, Deba Pratim. Design of a Wearable Two-Dimensional Joystick as a Muscle-Machine Interface Using Mechanomyographic Signals.

Degree: MS, Electrical and Computer Engineering, 2013, Virginia Tech

 Finger gesture recognition using glove-like interfaces are very accurate for sensing individual finger positions by employing a gamut of sensors. However, for the same reason,… (more)

Subjects/Keywords: Gesture Recognition; Wearable Joystick; Mechanomyography; Pattern Recognition

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

APA (6th Edition):

Saha, D. P. (2013). Design of a Wearable Two-Dimensional Joystick as a Muscle-Machine Interface Using Mechanomyographic Signals. (Masters Thesis). Virginia Tech. Retrieved from http://hdl.handle.net/10919/78044

Chicago Manual of Style (16th Edition):

Saha, Deba Pratim. “Design of a Wearable Two-Dimensional Joystick as a Muscle-Machine Interface Using Mechanomyographic Signals.” 2013. Masters Thesis, Virginia Tech. Accessed May 26, 2019. http://hdl.handle.net/10919/78044.

MLA Handbook (7th Edition):

Saha, Deba Pratim. “Design of a Wearable Two-Dimensional Joystick as a Muscle-Machine Interface Using Mechanomyographic Signals.” 2013. Web. 26 May 2019.

Vancouver:

Saha DP. Design of a Wearable Two-Dimensional Joystick as a Muscle-Machine Interface Using Mechanomyographic Signals. [Internet] [Masters thesis]. Virginia Tech; 2013. [cited 2019 May 26]. Available from: http://hdl.handle.net/10919/78044.

Council of Science Editors:

Saha DP. Design of a Wearable Two-Dimensional Joystick as a Muscle-Machine Interface Using Mechanomyographic Signals. [Masters Thesis]. Virginia Tech; 2013. Available from: http://hdl.handle.net/10919/78044


North Carolina State University

21. Miao, Shun. 3D face recognition from range images.

Degree: MS, Electrical Engineering, 2010, North Carolina State University

 In this thesis, we explore the statistical and geometrical behavior of uncontrolled parameters of human face, including both rigid transform caused by head pose and… (more)

Subjects/Keywords: geodesic; segmentation; face recognition; pattern recognition

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APA (6th Edition):

Miao, S. (2010). 3D face recognition from range images. (Thesis). North Carolina State University. Retrieved from http://www.lib.ncsu.edu/resolver/1840.16/6295

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):

Miao, Shun. “3D face recognition from range images.” 2010. Thesis, North Carolina State University. Accessed May 26, 2019. http://www.lib.ncsu.edu/resolver/1840.16/6295.

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

MLA Handbook (7th Edition):

Miao, Shun. “3D face recognition from range images.” 2010. Web. 26 May 2019.

Vancouver:

Miao S. 3D face recognition from range images. [Internet] [Thesis]. North Carolina State University; 2010. [cited 2019 May 26]. Available from: http://www.lib.ncsu.edu/resolver/1840.16/6295.

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

Council of Science Editors:

Miao S. 3D face recognition from range images. [Thesis]. North Carolina State University; 2010. Available from: http://www.lib.ncsu.edu/resolver/1840.16/6295

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


University of Central Florida

22. Liu, Jingen. Learning Semantic Features For Visual Recognition.

Degree: 2009, University of Central Florida

 Visual recognition (e.g., object, scene and action recognition) is an active area of research in computer vision due to its increasing number of real-world applications… (more)

Subjects/Keywords: visual recognition; action recognition; scene recognition; pattern recognition; Computer Sciences; Engineering

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APA (6th Edition):

Liu, J. (2009). Learning Semantic Features For Visual Recognition. (Doctoral Dissertation). University of Central Florida. Retrieved from http://stars.library.ucf.edu/etd/4002

Chicago Manual of Style (16th Edition):

Liu, Jingen. “Learning Semantic Features For Visual Recognition.” 2009. Doctoral Dissertation, University of Central Florida. Accessed May 26, 2019. http://stars.library.ucf.edu/etd/4002.

MLA Handbook (7th Edition):

Liu, Jingen. “Learning Semantic Features For Visual Recognition.” 2009. Web. 26 May 2019.

Vancouver:

Liu J. Learning Semantic Features For Visual Recognition. [Internet] [Doctoral dissertation]. University of Central Florida; 2009. [cited 2019 May 26]. Available from: http://stars.library.ucf.edu/etd/4002.

Council of Science Editors:

Liu J. Learning Semantic Features For Visual Recognition. [Doctoral Dissertation]. University of Central Florida; 2009. Available from: http://stars.library.ucf.edu/etd/4002


Oregon State University

23. You, Zeyu. A statistical inference framework for finding recurring patterns in large data with applications to energy management.

Degree: MS, Electrical and Computer Engineering, 2014, Oregon State University

 We consider the problem of finding unknown patterns that are recurring across multiple sets. For example, finding multiple objects that are present in multiple images… (more)

Subjects/Keywords: recurring pattern recognition; Pattern recognition systems  – Mathematical models

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

APA (6th Edition):

You, Z. (2014). A statistical inference framework for finding recurring patterns in large data with applications to energy management. (Masters Thesis). Oregon State University. Retrieved from http://hdl.handle.net/1957/50023

Chicago Manual of Style (16th Edition):

You, Zeyu. “A statistical inference framework for finding recurring patterns in large data with applications to energy management.” 2014. Masters Thesis, Oregon State University. Accessed May 26, 2019. http://hdl.handle.net/1957/50023.

MLA Handbook (7th Edition):

You, Zeyu. “A statistical inference framework for finding recurring patterns in large data with applications to energy management.” 2014. Web. 26 May 2019.

Vancouver:

You Z. A statistical inference framework for finding recurring patterns in large data with applications to energy management. [Internet] [Masters thesis]. Oregon State University; 2014. [cited 2019 May 26]. Available from: http://hdl.handle.net/1957/50023.

Council of Science Editors:

You Z. A statistical inference framework for finding recurring patterns in large data with applications to energy management. [Masters Thesis]. Oregon State University; 2014. Available from: http://hdl.handle.net/1957/50023


Portland State University

24. Sharma, Karan. The Link Between Image Segmentation and Image Recognition.

Degree: MS(M.S.) in Computer Science, Computer Science, 2012, Portland State University

  A long standing debate in computer vision community concerns the link between segmentation and recognition. The question I am trying to answer here is,… (more)

Subjects/Keywords: Image segmentation; Scalability; Recognition algorithms; Computer vision; Pattern recognition systems; Image processing; Optical pattern recognition

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APA (6th Edition):

Sharma, K. (2012). The Link Between Image Segmentation and Image Recognition. (Masters Thesis). Portland State University. Retrieved from https://pdxscholar.library.pdx.edu/open_access_etds/199

Chicago Manual of Style (16th Edition):

Sharma, Karan. “The Link Between Image Segmentation and Image Recognition.” 2012. Masters Thesis, Portland State University. Accessed May 26, 2019. https://pdxscholar.library.pdx.edu/open_access_etds/199.

MLA Handbook (7th Edition):

Sharma, Karan. “The Link Between Image Segmentation and Image Recognition.” 2012. Web. 26 May 2019.

Vancouver:

Sharma K. The Link Between Image Segmentation and Image Recognition. [Internet] [Masters thesis]. Portland State University; 2012. [cited 2019 May 26]. Available from: https://pdxscholar.library.pdx.edu/open_access_etds/199.

Council of Science Editors:

Sharma K. The Link Between Image Segmentation and Image Recognition. [Masters Thesis]. Portland State University; 2012. Available from: https://pdxscholar.library.pdx.edu/open_access_etds/199


Florida Atlantic University

25. Huang, Lin. Automated biometrics of audio-visual multiple modals.

Degree: PhD, 2010, Florida Atlantic University

Summary: Biometrics is the science and technology of measuring and analyzing biological data for authentication purposes. Its progress has brought in a large number of… (more)

Subjects/Keywords: Pattern recognition systems; Optical pattern recognition; Biometric identification; Identification – Automation; Automatic speech recognition

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

APA (6th Edition):

Huang, L. (2010). Automated biometrics of audio-visual multiple modals. (Doctoral Dissertation). Florida Atlantic University. Retrieved from http://purl.flvc.org/FAU/1927864

Chicago Manual of Style (16th Edition):

Huang, Lin. “Automated biometrics of audio-visual multiple modals.” 2010. Doctoral Dissertation, Florida Atlantic University. Accessed May 26, 2019. http://purl.flvc.org/FAU/1927864.

MLA Handbook (7th Edition):

Huang, Lin. “Automated biometrics of audio-visual multiple modals.” 2010. Web. 26 May 2019.

Vancouver:

Huang L. Automated biometrics of audio-visual multiple modals. [Internet] [Doctoral dissertation]. Florida Atlantic University; 2010. [cited 2019 May 26]. Available from: http://purl.flvc.org/FAU/1927864.

Council of Science Editors:

Huang L. Automated biometrics of audio-visual multiple modals. [Doctoral Dissertation]. Florida Atlantic University; 2010. Available from: http://purl.flvc.org/FAU/1927864


University of Dayton

26. Tompkins, Richard Cortland. Multimodal recognition using simultaneous images of iris and face with opportunistic feature selection.

Degree: PhD, Electrical Engineering, 2011, University of Dayton

  Techniques for establishing a person7#8217;s identity are characterized by several shortcomings. Identification documents may be forged or altered, signatures are difficult to authenticate and… (more)

Subjects/Keywords: Electrical Engineering; biometrics; computer vision; face recognition; iris recognition; pattern recognition

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APA (6th Edition):

Tompkins, R. C. (2011). Multimodal recognition using simultaneous images of iris and face with opportunistic feature selection. (Doctoral Dissertation). University of Dayton. Retrieved from http://rave.ohiolink.edu/etdc/view?acc_num=dayton1312222279

Chicago Manual of Style (16th Edition):

Tompkins, Richard Cortland. “Multimodal recognition using simultaneous images of iris and face with opportunistic feature selection.” 2011. Doctoral Dissertation, University of Dayton. Accessed May 26, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=dayton1312222279.

MLA Handbook (7th Edition):

Tompkins, Richard Cortland. “Multimodal recognition using simultaneous images of iris and face with opportunistic feature selection.” 2011. Web. 26 May 2019.

Vancouver:

Tompkins RC. Multimodal recognition using simultaneous images of iris and face with opportunistic feature selection. [Internet] [Doctoral dissertation]. University of Dayton; 2011. [cited 2019 May 26]. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=dayton1312222279.

Council of Science Editors:

Tompkins RC. Multimodal recognition using simultaneous images of iris and face with opportunistic feature selection. [Doctoral Dissertation]. University of Dayton; 2011. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=dayton1312222279


University of Southern Queensland

27. Hu, Hong. Accurate and robust algorithms for microarray data classification.

Degree: 2008, University of Southern Queensland

 [Abstract]Microarray data classification is used primarily to predict unseen data using a model built on categorized existing Microarray data. One of the major challenges is… (more)

Subjects/Keywords: 280207 Pattern Recognition

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APA (6th Edition):

Hu, H. (2008). Accurate and robust algorithms for microarray data classification. (Thesis). University of Southern Queensland. Retrieved from http://eprints.usq.edu.au/6221/1/Hu_2008_front.pdf ; http://eprints.usq.edu.au/6221/2/Hu_2008_whole.pdf

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):

Hu, Hong. “Accurate and robust algorithms for microarray data classification.” 2008. Thesis, University of Southern Queensland. Accessed May 26, 2019. http://eprints.usq.edu.au/6221/1/Hu_2008_front.pdf ; http://eprints.usq.edu.au/6221/2/Hu_2008_whole.pdf.

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

MLA Handbook (7th Edition):

Hu, Hong. “Accurate and robust algorithms for microarray data classification.” 2008. Web. 26 May 2019.

Vancouver:

Hu H. Accurate and robust algorithms for microarray data classification. [Internet] [Thesis]. University of Southern Queensland; 2008. [cited 2019 May 26]. Available from: http://eprints.usq.edu.au/6221/1/Hu_2008_front.pdf ; http://eprints.usq.edu.au/6221/2/Hu_2008_whole.pdf.

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

Council of Science Editors:

Hu H. Accurate and robust algorithms for microarray data classification. [Thesis]. University of Southern Queensland; 2008. Available from: http://eprints.usq.edu.au/6221/1/Hu_2008_front.pdf ; http://eprints.usq.edu.au/6221/2/Hu_2008_whole.pdf

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


University of Exeter

28. Schmolck, Alexander. Smooth relevance vector machines.

Degree: PhD, 2008, University of Exeter

 Regression tasks belong to the set of core problems faced in statistics and machine learning and promising approaches can often be generalized to also deal… (more)

Subjects/Keywords: 006.4; Pattern Recognition : Kernel methods : Wavelet shrinkage

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APA (6th Edition):

Schmolck, A. (2008). Smooth relevance vector machines. (Doctoral Dissertation). University of Exeter. Retrieved from http://hdl.handle.net/10036/40793

Chicago Manual of Style (16th Edition):

Schmolck, Alexander. “Smooth relevance vector machines.” 2008. Doctoral Dissertation, University of Exeter. Accessed May 26, 2019. http://hdl.handle.net/10036/40793.

MLA Handbook (7th Edition):

Schmolck, Alexander. “Smooth relevance vector machines.” 2008. Web. 26 May 2019.

Vancouver:

Schmolck A. Smooth relevance vector machines. [Internet] [Doctoral dissertation]. University of Exeter; 2008. [cited 2019 May 26]. Available from: http://hdl.handle.net/10036/40793.

Council of Science Editors:

Schmolck A. Smooth relevance vector machines. [Doctoral Dissertation]. University of Exeter; 2008. Available from: http://hdl.handle.net/10036/40793


Texas A&M University

29. Fields, Matthew James. Facilitation of visual pattern recognition by extraction of relevant features from microscopic traffic data.

Degree: 2009, Texas A&M University

 An experimental approach to traffic flow analysis is presented in which methodology from pattern recognition is applied to a specific dataset to examine its utility… (more)

Subjects/Keywords: Pattern Recognition; Feature Extraction; Microscopic Traffic

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APA (6th Edition):

Fields, M. J. (2009). Facilitation of visual pattern recognition by extraction of relevant features from microscopic traffic data. (Thesis). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/ETD-TAMU-2036

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):

Fields, Matthew James. “Facilitation of visual pattern recognition by extraction of relevant features from microscopic traffic data.” 2009. Thesis, Texas A&M University. Accessed May 26, 2019. http://hdl.handle.net/1969.1/ETD-TAMU-2036.

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

MLA Handbook (7th Edition):

Fields, Matthew James. “Facilitation of visual pattern recognition by extraction of relevant features from microscopic traffic data.” 2009. Web. 26 May 2019.

Vancouver:

Fields MJ. Facilitation of visual pattern recognition by extraction of relevant features from microscopic traffic data. [Internet] [Thesis]. Texas A&M University; 2009. [cited 2019 May 26]. Available from: http://hdl.handle.net/1969.1/ETD-TAMU-2036.

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

Council of Science Editors:

Fields MJ. Facilitation of visual pattern recognition by extraction of relevant features from microscopic traffic data. [Thesis]. Texas A&M University; 2009. Available from: http://hdl.handle.net/1969.1/ETD-TAMU-2036

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


Victoria University of Wellington

30. Lin, Wei-Chuan. Exploiting Radio Irregularity in Wireless Networks for Automated People Counting.

Degree: 2013, Victoria University of Wellington

 Wireless devices exist almost everywhere in our daily life. Wireless communications, which is an integral part of wireless devices, suffers from radio irregularity – a… (more)

Subjects/Keywords: People counting; Wireless networks; Overcomplete pattern recognition

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

APA (6th Edition):

Lin, W. (2013). Exploiting Radio Irregularity in Wireless Networks for Automated People Counting. (Masters Thesis). Victoria University of Wellington. Retrieved from http://hdl.handle.net/10063/2833

Chicago Manual of Style (16th Edition):

Lin, Wei-Chuan. “Exploiting Radio Irregularity in Wireless Networks for Automated People Counting.” 2013. Masters Thesis, Victoria University of Wellington. Accessed May 26, 2019. http://hdl.handle.net/10063/2833.

MLA Handbook (7th Edition):

Lin, Wei-Chuan. “Exploiting Radio Irregularity in Wireless Networks for Automated People Counting.” 2013. Web. 26 May 2019.

Vancouver:

Lin W. Exploiting Radio Irregularity in Wireless Networks for Automated People Counting. [Internet] [Masters thesis]. Victoria University of Wellington; 2013. [cited 2019 May 26]. Available from: http://hdl.handle.net/10063/2833.

Council of Science Editors:

Lin W. Exploiting Radio Irregularity in Wireless Networks for Automated People Counting. [Masters Thesis]. Victoria University of Wellington; 2013. Available from: http://hdl.handle.net/10063/2833

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