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You searched for +publisher:"Georgia Tech" +contributor:("Lee, Chin-Hui"). Showing records 1 – 30 of 30 total matches.

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1. Khire, Sourabh Mohan. Time-sensitive communication of digital images, with applications in telepathology.

Degree: MS, Electrical and Computer Engineering, 2009, Georgia Tech

 Telepathology is defined as the practice of pathology at a distance using video imaging and telecommunications. In this thesis we address the two main technology… (more)

Subjects/Keywords: Image transmission; Image compression; Telepathology; Whole slide images; Digital images; Diagnostic imaging; Image compression; Data transmission systems

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APA (6th Edition):

Khire, S. M. (2009). Time-sensitive communication of digital images, with applications in telepathology. (Masters Thesis). Georgia Tech. Retrieved from http://hdl.handle.net/1853/29761

Chicago Manual of Style (16th Edition):

Khire, Sourabh Mohan. “Time-sensitive communication of digital images, with applications in telepathology.” 2009. Masters Thesis, Georgia Tech. Accessed September 22, 2019. http://hdl.handle.net/1853/29761.

MLA Handbook (7th Edition):

Khire, Sourabh Mohan. “Time-sensitive communication of digital images, with applications in telepathology.” 2009. Web. 22 Sep 2019.

Vancouver:

Khire SM. Time-sensitive communication of digital images, with applications in telepathology. [Internet] [Masters thesis]. Georgia Tech; 2009. [cited 2019 Sep 22]. Available from: http://hdl.handle.net/1853/29761.

Council of Science Editors:

Khire SM. Time-sensitive communication of digital images, with applications in telepathology. [Masters Thesis]. Georgia Tech; 2009. Available from: http://hdl.handle.net/1853/29761


Georgia Tech

2. Xiong, Cong. Energy-efficient design in wireless communications networks.

Degree: PhD, Electrical and Computer Engineering, 2014, Georgia Tech

 The widespread application of wireless services and the requirements of ubiquitous access have recently triggered rapidly booming energy consumption in wireless communications networks. Such escalation… (more)

Subjects/Keywords: Energy efficiency; Spectral efficiency; OFDMA; Cognitive radio; Two-way relay

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APA (6th Edition):

Xiong, C. (2014). Energy-efficient design in wireless communications networks. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/52217

Chicago Manual of Style (16th Edition):

Xiong, Cong. “Energy-efficient design in wireless communications networks.” 2014. Doctoral Dissertation, Georgia Tech. Accessed September 22, 2019. http://hdl.handle.net/1853/52217.

MLA Handbook (7th Edition):

Xiong, Cong. “Energy-efficient design in wireless communications networks.” 2014. Web. 22 Sep 2019.

Vancouver:

Xiong C. Energy-efficient design in wireless communications networks. [Internet] [Doctoral dissertation]. Georgia Tech; 2014. [cited 2019 Sep 22]. Available from: http://hdl.handle.net/1853/52217.

Council of Science Editors:

Xiong C. Energy-efficient design in wireless communications networks. [Doctoral Dissertation]. Georgia Tech; 2014. Available from: http://hdl.handle.net/1853/52217


Georgia Tech

3. Kim, Pilho. E-model: event-based graph data model theory and implementation.

Degree: PhD, Electrical and Computer Engineering, 2009, Georgia Tech

 The necessity of managing disparate data models is increasing within all IT areas. Emerging hybrid relational-XML systems are under development in this context to support… (more)

Subjects/Keywords: Database architectures; Multimedia databases; Modeling structured; Textual and multimedia data; Graphs and networks; Linked representations; Modeling and management; Data models; Database models; Schema and subschema; Data translation; Database design; Data structures (Computer science); Databases; Multimedia systems; Application program interfaces (Computer software)

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APA (6th Edition):

Kim, P. (2009). E-model: event-based graph data model theory and implementation. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/29608

Chicago Manual of Style (16th Edition):

Kim, Pilho. “E-model: event-based graph data model theory and implementation.” 2009. Doctoral Dissertation, Georgia Tech. Accessed September 22, 2019. http://hdl.handle.net/1853/29608.

MLA Handbook (7th Edition):

Kim, Pilho. “E-model: event-based graph data model theory and implementation.” 2009. Web. 22 Sep 2019.

Vancouver:

Kim P. E-model: event-based graph data model theory and implementation. [Internet] [Doctoral dissertation]. Georgia Tech; 2009. [cited 2019 Sep 22]. Available from: http://hdl.handle.net/1853/29608.

Council of Science Editors:

Kim P. E-model: event-based graph data model theory and implementation. [Doctoral Dissertation]. Georgia Tech; 2009. Available from: http://hdl.handle.net/1853/29608


Georgia Tech

4. Ma, Chengyuan. A detection-based pattern recognition framework and its applications.

Degree: PhD, Electrical and Computer Engineering, 2010, Georgia Tech

 The objective of this dissertation is to present a detection-based pattern recognition framework and demonstrate its applications in automatic speech recognition and broadcast news video… (more)

Subjects/Keywords: Speech recognition; Detection-based; Evidence fusion; Pattern recognition systems; Automatic speech recognition; Digital video

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APA (6th Edition):

Ma, C. (2010). A detection-based pattern recognition framework and its applications. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/33889

Chicago Manual of Style (16th Edition):

Ma, Chengyuan. “A detection-based pattern recognition framework and its applications.” 2010. Doctoral Dissertation, Georgia Tech. Accessed September 22, 2019. http://hdl.handle.net/1853/33889.

MLA Handbook (7th Edition):

Ma, Chengyuan. “A detection-based pattern recognition framework and its applications.” 2010. Web. 22 Sep 2019.

Vancouver:

Ma C. A detection-based pattern recognition framework and its applications. [Internet] [Doctoral dissertation]. Georgia Tech; 2010. [cited 2019 Sep 22]. Available from: http://hdl.handle.net/1853/33889.

Council of Science Editors:

Ma C. A detection-based pattern recognition framework and its applications. [Doctoral Dissertation]. Georgia Tech; 2010. Available from: http://hdl.handle.net/1853/33889

5. Byun, Byungki. On discriminative semi-supervised incremental learning with a multi-view perspective for image concept modeling.

Degree: PhD, Electrical and Computer Engineering, 2012, Georgia Tech

 This dissertation presents the development of a semi-supervised incremental learning framework with a multi-view perspective for image concept modeling. For reliable image concept characterization, having… (more)

Subjects/Keywords: Discriminative learning; Semi-supervised learning; Incremental learning; Image modeling; Multi-view learning; Machine learning; Supervised learning (Machine learning); Boosting (Algorithms)

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APA (6th Edition):

Byun, B. (2012). On discriminative semi-supervised incremental learning with a multi-view perspective for image concept modeling. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/43597

Chicago Manual of Style (16th Edition):

Byun, Byungki. “On discriminative semi-supervised incremental learning with a multi-view perspective for image concept modeling.” 2012. Doctoral Dissertation, Georgia Tech. Accessed September 22, 2019. http://hdl.handle.net/1853/43597.

MLA Handbook (7th Edition):

Byun, Byungki. “On discriminative semi-supervised incremental learning with a multi-view perspective for image concept modeling.” 2012. Web. 22 Sep 2019.

Vancouver:

Byun B. On discriminative semi-supervised incremental learning with a multi-view perspective for image concept modeling. [Internet] [Doctoral dissertation]. Georgia Tech; 2012. [cited 2019 Sep 22]. Available from: http://hdl.handle.net/1853/43597.

Council of Science Editors:

Byun B. On discriminative semi-supervised incremental learning with a multi-view perspective for image concept modeling. [Doctoral Dissertation]. Georgia Tech; 2012. Available from: http://hdl.handle.net/1853/43597


Georgia Tech

6. Chen, Shiyang. Spatiotemporal modeling of brain dynamics using machine learning approaches.

Degree: PhD, Biomedical Engineering (Joint GT/Emory Department), 2017, Georgia Tech

 Resting state fMRI (rfMRI) has been widely used to study functional connectivity of human brains. Although most of the analysis methods to date have assumed… (more)

Subjects/Keywords: Functional magnetic resonance imaging; Resting-state; Dynamic model; Individual identification; Gated recurrent unit; Recurrent neural network

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APA (6th Edition):

Chen, S. (2017). Spatiotemporal modeling of brain dynamics using machine learning approaches. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/60677

Chicago Manual of Style (16th Edition):

Chen, Shiyang. “Spatiotemporal modeling of brain dynamics using machine learning approaches.” 2017. Doctoral Dissertation, Georgia Tech. Accessed September 22, 2019. http://hdl.handle.net/1853/60677.

MLA Handbook (7th Edition):

Chen, Shiyang. “Spatiotemporal modeling of brain dynamics using machine learning approaches.” 2017. Web. 22 Sep 2019.

Vancouver:

Chen S. Spatiotemporal modeling of brain dynamics using machine learning approaches. [Internet] [Doctoral dissertation]. Georgia Tech; 2017. [cited 2019 Sep 22]. Available from: http://hdl.handle.net/1853/60677.

Council of Science Editors:

Chen S. Spatiotemporal modeling of brain dynamics using machine learning approaches. [Doctoral Dissertation]. Georgia Tech; 2017. Available from: http://hdl.handle.net/1853/60677


Georgia Tech

7. Meng, Zhong. Discriminative and adaptive training for robust speech recognition and understanding.

Degree: PhD, Electrical and Computer Engineering, 2018, Georgia Tech

 Robust automatic speech recognition (ASR) and understanding (ASU) under various conditions remains to be a challenging problem even with the advances of deep learning. To… (more)

Subjects/Keywords: Discriminative training; Adaptation; Deep neural network; Acoustic model

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APA (6th Edition):

Meng, Z. (2018). Discriminative and adaptive training for robust speech recognition and understanding. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/60262

Chicago Manual of Style (16th Edition):

Meng, Zhong. “Discriminative and adaptive training for robust speech recognition and understanding.” 2018. Doctoral Dissertation, Georgia Tech. Accessed September 22, 2019. http://hdl.handle.net/1853/60262.

MLA Handbook (7th Edition):

Meng, Zhong. “Discriminative and adaptive training for robust speech recognition and understanding.” 2018. Web. 22 Sep 2019.

Vancouver:

Meng Z. Discriminative and adaptive training for robust speech recognition and understanding. [Internet] [Doctoral dissertation]. Georgia Tech; 2018. [cited 2019 Sep 22]. Available from: http://hdl.handle.net/1853/60262.

Council of Science Editors:

Meng Z. Discriminative and adaptive training for robust speech recognition and understanding. [Doctoral Dissertation]. Georgia Tech; 2018. Available from: http://hdl.handle.net/1853/60262


Georgia Tech

8. Chen, I-Fan. Resource-dependent acoustic and language modeling for spoken keyword search.

Degree: PhD, Electrical and Computer Engineering, 2015, Georgia Tech

 In this dissertation, three research directions were explored to alleviate two major issues, i.e., the use of incorrect models and training/test condition mismatches, in the… (more)

Subjects/Keywords: Spoken keyword search; Keyword spotting; Acoustic model; Language model; Speech recognition

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APA (6th Edition):

Chen, I. (2015). Resource-dependent acoustic and language modeling for spoken keyword search. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/54919

Chicago Manual of Style (16th Edition):

Chen, I-Fan. “Resource-dependent acoustic and language modeling for spoken keyword search.” 2015. Doctoral Dissertation, Georgia Tech. Accessed September 22, 2019. http://hdl.handle.net/1853/54919.

MLA Handbook (7th Edition):

Chen, I-Fan. “Resource-dependent acoustic and language modeling for spoken keyword search.” 2015. Web. 22 Sep 2019.

Vancouver:

Chen I. Resource-dependent acoustic and language modeling for spoken keyword search. [Internet] [Doctoral dissertation]. Georgia Tech; 2015. [cited 2019 Sep 22]. Available from: http://hdl.handle.net/1853/54919.

Council of Science Editors:

Chen I. Resource-dependent acoustic and language modeling for spoken keyword search. [Doctoral Dissertation]. Georgia Tech; 2015. Available from: http://hdl.handle.net/1853/54919

9. Shakil, Sadia. Windowing effects and adaptive change point detection of dynamic functional connectivity in the brain.

Degree: PhD, Electrical and Computer Engineering, 2016, Georgia Tech

 Evidence of networks in the resting-brain reflecting the spontaneous brain activity is perhaps the most significant discovery to understand intrinsic brain functionality. Moreover, subsequent detection… (more)

Subjects/Keywords: Dynamic functional connectivity; Sliding window correlation; Adaptive change point detection; Network dynamics

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APA (6th Edition):

Shakil, S. (2016). Windowing effects and adaptive change point detection of dynamic functional connectivity in the brain. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/55006

Chicago Manual of Style (16th Edition):

Shakil, Sadia. “Windowing effects and adaptive change point detection of dynamic functional connectivity in the brain.” 2016. Doctoral Dissertation, Georgia Tech. Accessed September 22, 2019. http://hdl.handle.net/1853/55006.

MLA Handbook (7th Edition):

Shakil, Sadia. “Windowing effects and adaptive change point detection of dynamic functional connectivity in the brain.” 2016. Web. 22 Sep 2019.

Vancouver:

Shakil S. Windowing effects and adaptive change point detection of dynamic functional connectivity in the brain. [Internet] [Doctoral dissertation]. Georgia Tech; 2016. [cited 2019 Sep 22]. Available from: http://hdl.handle.net/1853/55006.

Council of Science Editors:

Shakil S. Windowing effects and adaptive change point detection of dynamic functional connectivity in the brain. [Doctoral Dissertation]. Georgia Tech; 2016. Available from: http://hdl.handle.net/1853/55006

10. Mushtaq, Aleem. An integrated approach to feature compensation combining particle filters and Hidden Markov Models for robust speech recognition.

Degree: PhD, Electrical and Computer Engineering, 2013, Georgia Tech

 The performance of automatic speech recognition systems often degrades in adverse conditions where there is a mismatch between training and testing conditions. This is true… (more)

Subjects/Keywords: Particle filter; Hidden Markov model; Robust speech recognition; Clustering; Markov chain Monte Carlo; Hidden Markov models; Speech perception; Monte Carlo method; Algorithms

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APA (6th Edition):

Mushtaq, A. (2013). An integrated approach to feature compensation combining particle filters and Hidden Markov Models for robust speech recognition. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/48982

Chicago Manual of Style (16th Edition):

Mushtaq, Aleem. “An integrated approach to feature compensation combining particle filters and Hidden Markov Models for robust speech recognition.” 2013. Doctoral Dissertation, Georgia Tech. Accessed September 22, 2019. http://hdl.handle.net/1853/48982.

MLA Handbook (7th Edition):

Mushtaq, Aleem. “An integrated approach to feature compensation combining particle filters and Hidden Markov Models for robust speech recognition.” 2013. Web. 22 Sep 2019.

Vancouver:

Mushtaq A. An integrated approach to feature compensation combining particle filters and Hidden Markov Models for robust speech recognition. [Internet] [Doctoral dissertation]. Georgia Tech; 2013. [cited 2019 Sep 22]. Available from: http://hdl.handle.net/1853/48982.

Council of Science Editors:

Mushtaq A. An integrated approach to feature compensation combining particle filters and Hidden Markov Models for robust speech recognition. [Doctoral Dissertation]. Georgia Tech; 2013. Available from: http://hdl.handle.net/1853/48982

11. Weng, Chao. Towards robust conversational speech recognition and understanding.

Degree: PhD, Electrical and Computer Engineering, 2014, Georgia Tech

 While significant progress has been made in automatic speech recognition (ASR) during the last few decades, recognizing and understanding unconstrained conversational speech remains a challenging… (more)

Subjects/Keywords: ASR; WFSTs; Robust speech recognition; Conversational speech; Speech understanding; Topic spotting; Deep neural networks

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APA (6th Edition):

Weng, C. (2014). Towards robust conversational speech recognition and understanding. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/52987

Chicago Manual of Style (16th Edition):

Weng, Chao. “Towards robust conversational speech recognition and understanding.” 2014. Doctoral Dissertation, Georgia Tech. Accessed September 22, 2019. http://hdl.handle.net/1853/52987.

MLA Handbook (7th Edition):

Weng, Chao. “Towards robust conversational speech recognition and understanding.” 2014. Web. 22 Sep 2019.

Vancouver:

Weng C. Towards robust conversational speech recognition and understanding. [Internet] [Doctoral dissertation]. Georgia Tech; 2014. [cited 2019 Sep 22]. Available from: http://hdl.handle.net/1853/52987.

Council of Science Editors:

Weng C. Towards robust conversational speech recognition and understanding. [Doctoral Dissertation]. Georgia Tech; 2014. Available from: http://hdl.handle.net/1853/52987

12. Kim, Ilseo. Per-exemplar analysis with MFoM fusion learning for multimedia retrieval and recounting.

Degree: PhD, Electrical and Computer Engineering, 2013, Georgia Tech

 As a large volume of digital video data becomes available, along with revolutionary advances in multimedia technologies, demand related to efficiently retrieving and recounting multimedia… (more)

Subjects/Keywords: MFoM; Optimization; Video retrieval

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APA (6th Edition):

Kim, I. (2013). Per-exemplar analysis with MFoM fusion learning for multimedia retrieval and recounting. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/52152

Chicago Manual of Style (16th Edition):

Kim, Ilseo. “Per-exemplar analysis with MFoM fusion learning for multimedia retrieval and recounting.” 2013. Doctoral Dissertation, Georgia Tech. Accessed September 22, 2019. http://hdl.handle.net/1853/52152.

MLA Handbook (7th Edition):

Kim, Ilseo. “Per-exemplar analysis with MFoM fusion learning for multimedia retrieval and recounting.” 2013. Web. 22 Sep 2019.

Vancouver:

Kim I. Per-exemplar analysis with MFoM fusion learning for multimedia retrieval and recounting. [Internet] [Doctoral dissertation]. Georgia Tech; 2013. [cited 2019 Sep 22]. Available from: http://hdl.handle.net/1853/52152.

Council of Science Editors:

Kim I. Per-exemplar analysis with MFoM fusion learning for multimedia retrieval and recounting. [Doctoral Dissertation]. Georgia Tech; 2013. Available from: http://hdl.handle.net/1853/52152

13. Reed, Jeremy T. Acoustic segment modeling and preference ranking for music information retrieval.

Degree: PhD, Electrical and Computer Engineering, 2010, Georgia Tech

 This dissertation focuses on improving content-based recommendation systems for music. Specifically, progress in the development in music content-based recommendation systems has stalled in recent years… (more)

Subjects/Keywords: Acoustic modeling; Music information retrieval; Preference ranking; Unsupervised learning; Acoustic segment modeling; Music and technology; Music and the Internet; Automatic speech recognition; Acoustic models

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APA (6th Edition):

Reed, J. T. (2010). Acoustic segment modeling and preference ranking for music information retrieval. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/37189

Chicago Manual of Style (16th Edition):

Reed, Jeremy T. “Acoustic segment modeling and preference ranking for music information retrieval.” 2010. Doctoral Dissertation, Georgia Tech. Accessed September 22, 2019. http://hdl.handle.net/1853/37189.

MLA Handbook (7th Edition):

Reed, Jeremy T. “Acoustic segment modeling and preference ranking for music information retrieval.” 2010. Web. 22 Sep 2019.

Vancouver:

Reed JT. Acoustic segment modeling and preference ranking for music information retrieval. [Internet] [Doctoral dissertation]. Georgia Tech; 2010. [cited 2019 Sep 22]. Available from: http://hdl.handle.net/1853/37189.

Council of Science Editors:

Reed JT. Acoustic segment modeling and preference ranking for music information retrieval. [Doctoral Dissertation]. Georgia Tech; 2010. Available from: http://hdl.handle.net/1853/37189

14. Torres, Juan Félix. Estimation of glottal source features from the spectral envelope of the acoustic speech signal.

Degree: PhD, Electrical and Computer Engineering, 2010, Georgia Tech

 Speech communication encompasses diverse types of information, including phonetics, affective state, voice quality, and speaker identity. From a speech production standpoint, the acoustic speech signal… (more)

Subjects/Keywords: Inverse filtering; Glottal waveform; Voice source; Speech processing; Glottalization (Phonetics); Speech synthesis; Machine learning; Supervised learning (Machine learning)

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APA (6th Edition):

Torres, J. F. (2010). Estimation of glottal source features from the spectral envelope of the acoustic speech signal. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/34736

Chicago Manual of Style (16th Edition):

Torres, Juan Félix. “Estimation of glottal source features from the spectral envelope of the acoustic speech signal.” 2010. Doctoral Dissertation, Georgia Tech. Accessed September 22, 2019. http://hdl.handle.net/1853/34736.

MLA Handbook (7th Edition):

Torres, Juan Félix. “Estimation of glottal source features from the spectral envelope of the acoustic speech signal.” 2010. Web. 22 Sep 2019.

Vancouver:

Torres JF. Estimation of glottal source features from the spectral envelope of the acoustic speech signal. [Internet] [Doctoral dissertation]. Georgia Tech; 2010. [cited 2019 Sep 22]. Available from: http://hdl.handle.net/1853/34736.

Council of Science Editors:

Torres JF. Estimation of glottal source features from the spectral envelope of the acoustic speech signal. [Doctoral Dissertation]. Georgia Tech; 2010. Available from: http://hdl.handle.net/1853/34736

15. Kalgaonkar, Kaustubh. Probabilistic space maps for speech with applications.

Degree: PhD, Electrical and Computer Engineering, 2011, Georgia Tech

 The objective of the proposed research is to develop a probabilistic model of speech production that exploits the multiplicity of mapping between the vocal tract… (more)

Subjects/Keywords: Automatic bandwidth expansion; Probabilistic space maps; Statistical models; Acoustic model adaptation; Speech enhancement; Speech perception; Speech processing systems

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APA (6th Edition):

Kalgaonkar, K. (2011). Probabilistic space maps for speech with applications. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/42739

Chicago Manual of Style (16th Edition):

Kalgaonkar, Kaustubh. “Probabilistic space maps for speech with applications.” 2011. Doctoral Dissertation, Georgia Tech. Accessed September 22, 2019. http://hdl.handle.net/1853/42739.

MLA Handbook (7th Edition):

Kalgaonkar, Kaustubh. “Probabilistic space maps for speech with applications.” 2011. Web. 22 Sep 2019.

Vancouver:

Kalgaonkar K. Probabilistic space maps for speech with applications. [Internet] [Doctoral dissertation]. Georgia Tech; 2011. [cited 2019 Sep 22]. Available from: http://hdl.handle.net/1853/42739.

Council of Science Editors:

Kalgaonkar K. Probabilistic space maps for speech with applications. [Doctoral Dissertation]. Georgia Tech; 2011. Available from: http://hdl.handle.net/1853/42739

16. Szwaykowska, Klementyna. Controlled Lagrangian particle tracking: analyzing the predictability of trajectories of autonomous agents in ocean flows.

Degree: PhD, Electrical and Computer Engineering, 2013, Georgia Tech

 Use of model-based path planning and navigation is a common strategy in mobile robotics. However, navigation performance may degrade in complex, time-varying environments under model… (more)

Subjects/Keywords: Stochastic systems; Error modeling; Underwater navigation; Underwater navigation; Error analysis (Mathematics); Mobile robots

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APA (6th Edition):

Szwaykowska, K. (2013). Controlled Lagrangian particle tracking: analyzing the predictability of trajectories of autonomous agents in ocean flows. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/50357

Chicago Manual of Style (16th Edition):

Szwaykowska, Klementyna. “Controlled Lagrangian particle tracking: analyzing the predictability of trajectories of autonomous agents in ocean flows.” 2013. Doctoral Dissertation, Georgia Tech. Accessed September 22, 2019. http://hdl.handle.net/1853/50357.

MLA Handbook (7th Edition):

Szwaykowska, Klementyna. “Controlled Lagrangian particle tracking: analyzing the predictability of trajectories of autonomous agents in ocean flows.” 2013. Web. 22 Sep 2019.

Vancouver:

Szwaykowska K. Controlled Lagrangian particle tracking: analyzing the predictability of trajectories of autonomous agents in ocean flows. [Internet] [Doctoral dissertation]. Georgia Tech; 2013. [cited 2019 Sep 22]. Available from: http://hdl.handle.net/1853/50357.

Council of Science Editors:

Szwaykowska K. Controlled Lagrangian particle tracking: analyzing the predictability of trajectories of autonomous agents in ocean flows. [Doctoral Dissertation]. Georgia Tech; 2013. Available from: http://hdl.handle.net/1853/50357

17. Ali, Asif. Voice query-by-example for resource-limited languages using an ergodic hidden Markov model of speech.

Degree: PhD, Electrical and Computer Engineering, 2013, Georgia Tech

 An ergodic hidden Markov model (EHMM) can be useful in extracting underlying structure embedded in connected speech without the need for a time-aligned transcribed corpus.… (more)

Subjects/Keywords: Speech recognition; Hidden Markov model; Ergodic theory; Hidden Markov models; Automatic speech recognition

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APA (6th Edition):

Ali, A. (2013). Voice query-by-example for resource-limited languages using an ergodic hidden Markov model of speech. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/50363

Chicago Manual of Style (16th Edition):

Ali, Asif. “Voice query-by-example for resource-limited languages using an ergodic hidden Markov model of speech.” 2013. Doctoral Dissertation, Georgia Tech. Accessed September 22, 2019. http://hdl.handle.net/1853/50363.

MLA Handbook (7th Edition):

Ali, Asif. “Voice query-by-example for resource-limited languages using an ergodic hidden Markov model of speech.” 2013. Web. 22 Sep 2019.

Vancouver:

Ali A. Voice query-by-example for resource-limited languages using an ergodic hidden Markov model of speech. [Internet] [Doctoral dissertation]. Georgia Tech; 2013. [cited 2019 Sep 22]. Available from: http://hdl.handle.net/1853/50363.

Council of Science Editors:

Ali A. Voice query-by-example for resource-limited languages using an ergodic hidden Markov model of speech. [Doctoral Dissertation]. Georgia Tech; 2013. Available from: http://hdl.handle.net/1853/50363

18. Tsao, Yu. An ensemble speaker and speaking environment modeling approach to robust speech recognition.

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

 In this study, an ensemble speaker and speaking environment modeling (ESSEM) approach is proposed to characterize environments in order to enhance performance robustness of automatic… (more)

Subjects/Keywords: Ensemble Speaker and Speaking Environment Modeling; ESSEM; Stochastic matching; Noise robustness; Environment modeling; Automatic speech recognition; Speech processing systems; Hidden Markov models

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APA (6th Edition):

Tsao, Y. (2008). An ensemble speaker and speaking environment modeling approach to robust speech recognition. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/26540

Chicago Manual of Style (16th Edition):

Tsao, Yu. “An ensemble speaker and speaking environment modeling approach to robust speech recognition.” 2008. Doctoral Dissertation, Georgia Tech. Accessed September 22, 2019. http://hdl.handle.net/1853/26540.

MLA Handbook (7th Edition):

Tsao, Yu. “An ensemble speaker and speaking environment modeling approach to robust speech recognition.” 2008. Web. 22 Sep 2019.

Vancouver:

Tsao Y. An ensemble speaker and speaking environment modeling approach to robust speech recognition. [Internet] [Doctoral dissertation]. Georgia Tech; 2008. [cited 2019 Sep 22]. Available from: http://hdl.handle.net/1853/26540.

Council of Science Editors:

Tsao Y. An ensemble speaker and speaking environment modeling approach to robust speech recognition. [Doctoral Dissertation]. Georgia Tech; 2008. Available from: http://hdl.handle.net/1853/26540

19. Vemulapalli, Smita. Audio-video based handwritten mathematical content recognition.

Degree: PhD, Electrical and Computer Engineering, 2012, Georgia Tech

 Recognizing handwritten mathematical content is a challenging problem, and more so when such content appears in classroom videos. However, given the fact that in such… (more)

Subjects/Keywords: Pattern recognition; Digital signal processing; Classifier combination; Signal processing Digital techniques; Image processing; Information retrieval; Pattern perception; Pattern recognition systems

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APA (6th Edition):

Vemulapalli, S. (2012). Audio-video based handwritten mathematical content recognition. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/45958

Chicago Manual of Style (16th Edition):

Vemulapalli, Smita. “Audio-video based handwritten mathematical content recognition.” 2012. Doctoral Dissertation, Georgia Tech. Accessed September 22, 2019. http://hdl.handle.net/1853/45958.

MLA Handbook (7th Edition):

Vemulapalli, Smita. “Audio-video based handwritten mathematical content recognition.” 2012. Web. 22 Sep 2019.

Vancouver:

Vemulapalli S. Audio-video based handwritten mathematical content recognition. [Internet] [Doctoral dissertation]. Georgia Tech; 2012. [cited 2019 Sep 22]. Available from: http://hdl.handle.net/1853/45958.

Council of Science Editors:

Vemulapalli S. Audio-video based handwritten mathematical content recognition. [Doctoral Dissertation]. Georgia Tech; 2012. Available from: http://hdl.handle.net/1853/45958

20. Zhao, Yong. Nonlinear compensation and heterogeneous data modeling for robust speech recognition.

Degree: PhD, Electrical and Computer Engineering, 2013, Georgia Tech

 The goal of robust speech recognition is to maintain satisfactory recognition accuracy under mismatched operating conditions. This dissertation addresses the robustness issue from two directions.… (more)

Subjects/Keywords: Robust speech recognition; Automatic speech recognition; Robust optimization

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APA (6th Edition):

Zhao, Y. (2013). Nonlinear compensation and heterogeneous data modeling for robust speech recognition. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/47566

Chicago Manual of Style (16th Edition):

Zhao, Yong. “Nonlinear compensation and heterogeneous data modeling for robust speech recognition.” 2013. Doctoral Dissertation, Georgia Tech. Accessed September 22, 2019. http://hdl.handle.net/1853/47566.

MLA Handbook (7th Edition):

Zhao, Yong. “Nonlinear compensation and heterogeneous data modeling for robust speech recognition.” 2013. Web. 22 Sep 2019.

Vancouver:

Zhao Y. Nonlinear compensation and heterogeneous data modeling for robust speech recognition. [Internet] [Doctoral dissertation]. Georgia Tech; 2013. [cited 2019 Sep 22]. Available from: http://hdl.handle.net/1853/47566.

Council of Science Editors:

Zhao Y. Nonlinear compensation and heterogeneous data modeling for robust speech recognition. [Doctoral Dissertation]. Georgia Tech; 2013. Available from: http://hdl.handle.net/1853/47566

21. Li, Xiangtao. High-speed analog-to-digital conversion in SiGe HBT technology.

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

 The objective of this research is to explore high-speed analog-to-digital converters (ADCs) using silicon-germanium (SiGe) heterojunction bipolar transistors (HBTs) for wireless digital receiver applications. The… (more)

Subjects/Keywords: ADC; Analog-to-digital converter; Track-and-hold amplifier; Sigma-delta modulator; Comparator; SiGe; Analog-to-digital converters; Heterojunctions; Bipolar transistors

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APA (6th Edition):

Li, X. (2008). High-speed analog-to-digital conversion in SiGe HBT technology. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/24652

Chicago Manual of Style (16th Edition):

Li, Xiangtao. “High-speed analog-to-digital conversion in SiGe HBT technology.” 2008. Doctoral Dissertation, Georgia Tech. Accessed September 22, 2019. http://hdl.handle.net/1853/24652.

MLA Handbook (7th Edition):

Li, Xiangtao. “High-speed analog-to-digital conversion in SiGe HBT technology.” 2008. Web. 22 Sep 2019.

Vancouver:

Li X. High-speed analog-to-digital conversion in SiGe HBT technology. [Internet] [Doctoral dissertation]. Georgia Tech; 2008. [cited 2019 Sep 22]. Available from: http://hdl.handle.net/1853/24652.

Council of Science Editors:

Li X. High-speed analog-to-digital conversion in SiGe HBT technology. [Doctoral Dissertation]. Georgia Tech; 2008. Available from: http://hdl.handle.net/1853/24652

22. Cheng, You-Chi. Robust gesture recognition.

Degree: PhD, Electrical and Computer Engineering, 2014, Georgia Tech

 It is a challenging problem to make a general hand gesture recognition system work in a practical operation environment. In this study, it is mainly… (more)

Subjects/Keywords: Gesture recognition; Robustness; Hidden Markov model; Model adaptation; Interpolation; Factor analysis

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APA (6th Edition):

Cheng, Y. (2014). Robust gesture recognition. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/53492

Chicago Manual of Style (16th Edition):

Cheng, You-Chi. “Robust gesture recognition.” 2014. Doctoral Dissertation, Georgia Tech. Accessed September 22, 2019. http://hdl.handle.net/1853/53492.

MLA Handbook (7th Edition):

Cheng, You-Chi. “Robust gesture recognition.” 2014. Web. 22 Sep 2019.

Vancouver:

Cheng Y. Robust gesture recognition. [Internet] [Doctoral dissertation]. Georgia Tech; 2014. [cited 2019 Sep 22]. Available from: http://hdl.handle.net/1853/53492.

Council of Science Editors:

Cheng Y. Robust gesture recognition. [Doctoral Dissertation]. Georgia Tech; 2014. Available from: http://hdl.handle.net/1853/53492

23. Huang, Zhen. Bayesian adaptation and combination of deep models for automatic speech recognition.

Degree: PhD, Electrical and Computer Engineering, 2017, Georgia Tech

 The objective of the proposed research is to deploy a Bayesian adaptation and combination framework for deep model based automatic speech recognition systems to combat… (more)

Subjects/Keywords: Deep neural networks

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APA (6th Edition):

Huang, Z. (2017). Bayesian adaptation and combination of deep models for automatic speech recognition. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/58653

Chicago Manual of Style (16th Edition):

Huang, Zhen. “Bayesian adaptation and combination of deep models for automatic speech recognition.” 2017. Doctoral Dissertation, Georgia Tech. Accessed September 22, 2019. http://hdl.handle.net/1853/58653.

MLA Handbook (7th Edition):

Huang, Zhen. “Bayesian adaptation and combination of deep models for automatic speech recognition.” 2017. Web. 22 Sep 2019.

Vancouver:

Huang Z. Bayesian adaptation and combination of deep models for automatic speech recognition. [Internet] [Doctoral dissertation]. Georgia Tech; 2017. [cited 2019 Sep 22]. Available from: http://hdl.handle.net/1853/58653.

Council of Science Editors:

Huang Z. Bayesian adaptation and combination of deep models for automatic speech recognition. [Doctoral Dissertation]. Georgia Tech; 2017. Available from: http://hdl.handle.net/1853/58653


Georgia Tech

24. Loeffler, Dominik B. Instrument Timbres and Pitch Estimation in Polyphonic Music.

Degree: MS, Electrical and Computer Engineering, 2006, Georgia Tech

 In the past decade, the availability of digitally encoded, downloadable music has increased dramatically, pushed mainly by the release of the now famous MP3 compression… (more)

Subjects/Keywords: Spectrogram; Psychoacoustics; Heuristic; Mixture model; Polyphonic; Timbre; EM; Pitch; GMM

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APA (6th Edition):

Loeffler, D. B. (2006). Instrument Timbres and Pitch Estimation in Polyphonic Music. (Masters Thesis). Georgia Tech. Retrieved from http://hdl.handle.net/1853/10568

Chicago Manual of Style (16th Edition):

Loeffler, Dominik B. “Instrument Timbres and Pitch Estimation in Polyphonic Music.” 2006. Masters Thesis, Georgia Tech. Accessed September 22, 2019. http://hdl.handle.net/1853/10568.

MLA Handbook (7th Edition):

Loeffler, Dominik B. “Instrument Timbres and Pitch Estimation in Polyphonic Music.” 2006. Web. 22 Sep 2019.

Vancouver:

Loeffler DB. Instrument Timbres and Pitch Estimation in Polyphonic Music. [Internet] [Masters thesis]. Georgia Tech; 2006. [cited 2019 Sep 22]. Available from: http://hdl.handle.net/1853/10568.

Council of Science Editors:

Loeffler DB. Instrument Timbres and Pitch Estimation in Polyphonic Music. [Masters Thesis]. Georgia Tech; 2006. Available from: http://hdl.handle.net/1853/10568


Georgia Tech

25. Smith, Paul Devon. An Analog Architecture for Auditory Feature Extraction and Recognition.

Degree: PhD, Electrical and Computer Engineering, 2004, Georgia Tech

 Speech recognition systems have been implemented using a wide range of signal processing techniques including neuromorphic/biological inspired and Digital Signal Processing techniques. Neuromorphic/biologically inspired techniques,… (more)

Subjects/Keywords: Neuromorphic cochlea; Hidden Markov Model (HMM); Cepstrum; Speech processing systems; Signal processing Digital techniques; Speech processing systems; Cochlea Models; Markov processes; Neural networks (Computer science)

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APA (6th Edition):

Smith, P. D. (2004). An Analog Architecture for Auditory Feature Extraction and Recognition. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/4839

Chicago Manual of Style (16th Edition):

Smith, Paul Devon. “An Analog Architecture for Auditory Feature Extraction and Recognition.” 2004. Doctoral Dissertation, Georgia Tech. Accessed September 22, 2019. http://hdl.handle.net/1853/4839.

MLA Handbook (7th Edition):

Smith, Paul Devon. “An Analog Architecture for Auditory Feature Extraction and Recognition.” 2004. Web. 22 Sep 2019.

Vancouver:

Smith PD. An Analog Architecture for Auditory Feature Extraction and Recognition. [Internet] [Doctoral dissertation]. Georgia Tech; 2004. [cited 2019 Sep 22]. Available from: http://hdl.handle.net/1853/4839.

Council of Science Editors:

Smith PD. An Analog Architecture for Auditory Feature Extraction and Recognition. [Doctoral Dissertation]. Georgia Tech; 2004. Available from: http://hdl.handle.net/1853/4839


Georgia Tech

26. Xie, Jiang (Linda). Mobility Management in Next Generation All-IP Based Wireless Systems.

Degree: PhD, Electrical and Computer Engineering, 2004, Georgia Tech

 Next generation wireless systems have an IP-based infrastructure with the support of heterogeneous access technologies. One research challenge for next generation all-IP based wireless systems… (more)

Subjects/Keywords: Mobility management; Signaling cost; Mobile IP; Quality of service; Resource management; Wireless overlay networks; Paging; Handoff management; Location management; Wireless communication systems Design and construction; Internet telephony; Beepers (Pagers); Artificial satellites in telecommunication

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APA (6th Edition):

Xie, J. (. (2004). Mobility Management in Next Generation All-IP Based Wireless Systems. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/5190

Chicago Manual of Style (16th Edition):

Xie, Jiang (Linda). “Mobility Management in Next Generation All-IP Based Wireless Systems.” 2004. Doctoral Dissertation, Georgia Tech. Accessed September 22, 2019. http://hdl.handle.net/1853/5190.

MLA Handbook (7th Edition):

Xie, Jiang (Linda). “Mobility Management in Next Generation All-IP Based Wireless Systems.” 2004. Web. 22 Sep 2019.

Vancouver:

Xie J(. Mobility Management in Next Generation All-IP Based Wireless Systems. [Internet] [Doctoral dissertation]. Georgia Tech; 2004. [cited 2019 Sep 22]. Available from: http://hdl.handle.net/1853/5190.

Council of Science Editors:

Xie J(. Mobility Management in Next Generation All-IP Based Wireless Systems. [Doctoral Dissertation]. Georgia Tech; 2004. Available from: http://hdl.handle.net/1853/5190


Georgia Tech

27. Mehta, Tejas R. Optimal, Multi-Modal Control with Applications in Robotics.

Degree: PhD, Electrical and Computer Engineering, 2007, Georgia Tech

 The objective of this dissertation is to incorporate the concept of optimality to multi-modal control and apply the theoretical results to obtain successful navigation strategies… (more)

Subjects/Keywords: Variational methods; Linguistic control of mobile robots; Optimal control; Multi-modal control; Hybrid systems; Autonomous robots; Mobile robots; Adaptive control systems; Automatic control

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APA (6th Edition):

Mehta, T. R. (2007). Optimal, Multi-Modal Control with Applications in Robotics. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/14628

Chicago Manual of Style (16th Edition):

Mehta, Tejas R. “Optimal, Multi-Modal Control with Applications in Robotics.” 2007. Doctoral Dissertation, Georgia Tech. Accessed September 22, 2019. http://hdl.handle.net/1853/14628.

MLA Handbook (7th Edition):

Mehta, Tejas R. “Optimal, Multi-Modal Control with Applications in Robotics.” 2007. Web. 22 Sep 2019.

Vancouver:

Mehta TR. Optimal, Multi-Modal Control with Applications in Robotics. [Internet] [Doctoral dissertation]. Georgia Tech; 2007. [cited 2019 Sep 22]. Available from: http://hdl.handle.net/1853/14628.

Council of Science Editors:

Mehta TR. Optimal, Multi-Modal Control with Applications in Robotics. [Doctoral Dissertation]. Georgia Tech; 2007. Available from: http://hdl.handle.net/1853/14628


Georgia Tech

28. Chen, Keke. Geometric Methods for Mining Large and Possibly Private Datasets.

Degree: PhD, Computing, 2006, Georgia Tech

 With the wide deployment of data intensive Internet applications and continued advances in sensing technology and biotechnology, large multidimensional datasets, possibly containing privacy-conscious information have… (more)

Subjects/Keywords: Geometric methods; Information visualization; Data mining; Privacy-preserving data mining; Data clustering; Data classification; Distributed collaborative data mining; Categorical data clustering

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APA (6th Edition):

Chen, K. (2006). Geometric Methods for Mining Large and Possibly Private Datasets. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/11561

Chicago Manual of Style (16th Edition):

Chen, Keke. “Geometric Methods for Mining Large and Possibly Private Datasets.” 2006. Doctoral Dissertation, Georgia Tech. Accessed September 22, 2019. http://hdl.handle.net/1853/11561.

MLA Handbook (7th Edition):

Chen, Keke. “Geometric Methods for Mining Large and Possibly Private Datasets.” 2006. Web. 22 Sep 2019.

Vancouver:

Chen K. Geometric Methods for Mining Large and Possibly Private Datasets. [Internet] [Doctoral dissertation]. Georgia Tech; 2006. [cited 2019 Sep 22]. Available from: http://hdl.handle.net/1853/11561.

Council of Science Editors:

Chen K. Geometric Methods for Mining Large and Possibly Private Datasets. [Doctoral Dissertation]. Georgia Tech; 2006. Available from: http://hdl.handle.net/1853/11561


Georgia Tech

29. 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 (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 September 22, 2019. 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. 22 Sep 2019.

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 2019 Sep 22]. 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

30. Pichon, Eric. Novel Methods for Multidimensional Image Segmentation.

Degree: PhD, Electrical and Computer Engineering, 2005, Georgia Tech

 Artificial vision is the problem of creating systems capable of processing visual information. A fundamental sub-problem of artificial vision is image segmentation, the problem of… (more)

Subjects/Keywords: Hamilton-Jacobi-Bellman equation; Biological vision; Laplace equation; Direction information; Hamilton-Jacobi equations; Image processing

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APA (6th Edition):

Pichon, E. (2005). Novel Methods for Multidimensional Image Segmentation. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/7504

Chicago Manual of Style (16th Edition):

Pichon, Eric. “Novel Methods for Multidimensional Image Segmentation.” 2005. Doctoral Dissertation, Georgia Tech. Accessed September 22, 2019. http://hdl.handle.net/1853/7504.

MLA Handbook (7th Edition):

Pichon, Eric. “Novel Methods for Multidimensional Image Segmentation.” 2005. Web. 22 Sep 2019.

Vancouver:

Pichon E. Novel Methods for Multidimensional Image Segmentation. [Internet] [Doctoral dissertation]. Georgia Tech; 2005. [cited 2019 Sep 22]. Available from: http://hdl.handle.net/1853/7504.

Council of Science Editors:

Pichon E. Novel Methods for Multidimensional Image Segmentation. [Doctoral Dissertation]. Georgia Tech; 2005. Available from: http://hdl.handle.net/1853/7504

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