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You searched for +publisher:"Georgia Tech" +contributor:("Moore, Elliot"). Showing records 1 – 16 of 16 total matches.

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Georgia Tech

1. Mathew, Melvin Julian. Automated Examination of Relative Afferent Pupillary Defect Using Pupil Detection and Tracking.

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

 In traditional clinical practice, medical professionals typically examine ocular conditions by conducting a series of procedures using various medical equipment, and these examinations are subject… (more)

Subjects/Keywords: Relative afferent pupillary defect; Pupil detection; Pupil measurement; Pupil examination

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APA (6th Edition):

Mathew, M. J. (2018). Automated Examination of Relative Afferent Pupillary Defect Using Pupil Detection and Tracking. (Masters Thesis). Georgia Tech. Retrieved from http://hdl.handle.net/1853/61629

Chicago Manual of Style (16th Edition):

Mathew, Melvin Julian. “Automated Examination of Relative Afferent Pupillary Defect Using Pupil Detection and Tracking.” 2018. Masters Thesis, Georgia Tech. Accessed September 17, 2019. http://hdl.handle.net/1853/61629.

MLA Handbook (7th Edition):

Mathew, Melvin Julian. “Automated Examination of Relative Afferent Pupillary Defect Using Pupil Detection and Tracking.” 2018. Web. 17 Sep 2019.

Vancouver:

Mathew MJ. Automated Examination of Relative Afferent Pupillary Defect Using Pupil Detection and Tracking. [Internet] [Masters thesis]. Georgia Tech; 2018. [cited 2019 Sep 17]. Available from: http://hdl.handle.net/1853/61629.

Council of Science Editors:

Mathew MJ. Automated Examination of Relative Afferent Pupillary Defect Using Pupil Detection and Tracking. [Masters Thesis]. Georgia Tech; 2018. Available from: http://hdl.handle.net/1853/61629


Georgia Tech

2. Kim, Jonathan Chongkang. Classification of affect using novel voice and visual features.

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

 Emotion adds an important element to the discussion of how information is conveyed and processed by humans; indeed, it plays an important role in the… (more)

Subjects/Keywords: Speech signal processing; Machine learning; Classifier fusion; Multimodal analysis; Emotion; Affective computing; Human behavior analysis; Speech production

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APA (6th Edition):

Kim, J. C. (2014). Classification of affect using novel voice and visual features. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/54301

Chicago Manual of Style (16th Edition):

Kim, Jonathan Chongkang. “Classification of affect using novel voice and visual features.” 2014. Doctoral Dissertation, Georgia Tech. Accessed September 17, 2019. http://hdl.handle.net/1853/54301.

MLA Handbook (7th Edition):

Kim, Jonathan Chongkang. “Classification of affect using novel voice and visual features.” 2014. Web. 17 Sep 2019.

Vancouver:

Kim JC. Classification of affect using novel voice and visual features. [Internet] [Doctoral dissertation]. Georgia Tech; 2014. [cited 2019 Sep 17]. Available from: http://hdl.handle.net/1853/54301.

Council of Science Editors:

Kim JC. Classification of affect using novel voice and visual features. [Doctoral Dissertation]. Georgia Tech; 2014. Available from: http://hdl.handle.net/1853/54301


Georgia Tech

3. Bishop, Shannon Renee Smith. Gabor and wavelet analysis with applications to Schatten class integral operators.

Degree: PhD, Mathematics, 2010, Georgia Tech

 This thesis addresses four topics in the area of applied harmonic analysis. First, we show that the affine densities of separable wavelet frames affect the… (more)

Subjects/Keywords: Wavelet frames; Fourier integral operators; Pseudodifferential operators; Gabor transform; Harmonic analysis; Wavelets (Mathematics); Fourier transformations

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APA (6th Edition):

Bishop, S. R. S. (2010). Gabor and wavelet analysis with applications to Schatten class integral operators. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/33976

Chicago Manual of Style (16th Edition):

Bishop, Shannon Renee Smith. “Gabor and wavelet analysis with applications to Schatten class integral operators.” 2010. Doctoral Dissertation, Georgia Tech. Accessed September 17, 2019. http://hdl.handle.net/1853/33976.

MLA Handbook (7th Edition):

Bishop, Shannon Renee Smith. “Gabor and wavelet analysis with applications to Schatten class integral operators.” 2010. Web. 17 Sep 2019.

Vancouver:

Bishop SRS. Gabor and wavelet analysis with applications to Schatten class integral operators. [Internet] [Doctoral dissertation]. Georgia Tech; 2010. [cited 2019 Sep 17]. Available from: http://hdl.handle.net/1853/33976.

Council of Science Editors:

Bishop SRS. Gabor and wavelet analysis with applications to Schatten class integral operators. [Doctoral Dissertation]. Georgia Tech; 2010. Available from: http://hdl.handle.net/1853/33976


Georgia Tech

4. 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 17, 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. 17 Sep 2019.

Vancouver:

Meng Z. Discriminative and adaptive training for robust speech recognition and understanding. [Internet] [Doctoral dissertation]. Georgia Tech; 2018. [cited 2019 Sep 17]. 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

5. Gupta, Udit. Towards development of no-reference objective measures for perceptual evaluation of singing voice separation.

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

 Singing Voice Separation (SVS) uses audio source separation methods to isolate the vocal component from the background accompaniment in a song mix. A key challenge… (more)

Subjects/Keywords: Source separation; Music information retrieval; Perceptual evaluation

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APA (6th Edition):

Gupta, U. (2017). Towards development of no-reference objective measures for perceptual evaluation of singing voice separation. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/59749

Chicago Manual of Style (16th Edition):

Gupta, Udit. “Towards development of no-reference objective measures for perceptual evaluation of singing voice separation.” 2017. Doctoral Dissertation, Georgia Tech. Accessed September 17, 2019. http://hdl.handle.net/1853/59749.

MLA Handbook (7th Edition):

Gupta, Udit. “Towards development of no-reference objective measures for perceptual evaluation of singing voice separation.” 2017. Web. 17 Sep 2019.

Vancouver:

Gupta U. Towards development of no-reference objective measures for perceptual evaluation of singing voice separation. [Internet] [Doctoral dissertation]. Georgia Tech; 2017. [cited 2019 Sep 17]. Available from: http://hdl.handle.net/1853/59749.

Council of Science Editors:

Gupta U. Towards development of no-reference objective measures for perceptual evaluation of singing voice separation. [Doctoral Dissertation]. Georgia Tech; 2017. Available from: http://hdl.handle.net/1853/59749


Georgia Tech

6. Gillespie, Stephanie Marie. Analysis of affective states from vocal acoustics in adults with aphasia.

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

 This research analyzed objective vocal acoustic measures of aphasic speech as they related to the detection or prediction of stress, depression, and emotional state in… (more)

Subjects/Keywords: Aphasia; Speech processing; Vocal acoustic; Glottal features; Teager features; Dysarthria

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APA (6th Edition):

Gillespie, S. M. (2017). Analysis of affective states from vocal acoustics in adults with aphasia. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/59794

Chicago Manual of Style (16th Edition):

Gillespie, Stephanie Marie. “Analysis of affective states from vocal acoustics in adults with aphasia.” 2017. Doctoral Dissertation, Georgia Tech. Accessed September 17, 2019. http://hdl.handle.net/1853/59794.

MLA Handbook (7th Edition):

Gillespie, Stephanie Marie. “Analysis of affective states from vocal acoustics in adults with aphasia.” 2017. Web. 17 Sep 2019.

Vancouver:

Gillespie SM. Analysis of affective states from vocal acoustics in adults with aphasia. [Internet] [Doctoral dissertation]. Georgia Tech; 2017. [cited 2019 Sep 17]. Available from: http://hdl.handle.net/1853/59794.

Council of Science Editors:

Gillespie SM. Analysis of affective states from vocal acoustics in adults with aphasia. [Doctoral Dissertation]. Georgia Tech; 2017. Available from: http://hdl.handle.net/1853/59794


Georgia Tech

7. Valentin, Giancarlo. Wearable Interfaces for Symbolic Communication by Working Dogs.

Degree: PhD, Electrical and Computer Engineering, 2019, Georgia Tech

 The objective of this dissertation is to develop wearable systems that allow working dogs to communicate accurately with humans. For example, a guide dog could… (more)

Subjects/Keywords: Wearable technology; Animal-Computer Interaction; Gesture recognition

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APA (6th Edition):

Valentin, G. (2019). Wearable Interfaces for Symbolic Communication by Working Dogs. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/61235

Chicago Manual of Style (16th Edition):

Valentin, Giancarlo. “Wearable Interfaces for Symbolic Communication by Working Dogs.” 2019. Doctoral Dissertation, Georgia Tech. Accessed September 17, 2019. http://hdl.handle.net/1853/61235.

MLA Handbook (7th Edition):

Valentin, Giancarlo. “Wearable Interfaces for Symbolic Communication by Working Dogs.” 2019. Web. 17 Sep 2019.

Vancouver:

Valentin G. Wearable Interfaces for Symbolic Communication by Working Dogs. [Internet] [Doctoral dissertation]. Georgia Tech; 2019. [cited 2019 Sep 17]. Available from: http://hdl.handle.net/1853/61235.

Council of Science Editors:

Valentin G. Wearable Interfaces for Symbolic Communication by Working Dogs. [Doctoral Dissertation]. Georgia Tech; 2019. Available from: http://hdl.handle.net/1853/61235

8. Rao, Hrishikesh. Paralinguistic event detection in children's speech.

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

 Paralinguistic events are useful indicators of the affective state of a speaker. These cues, in children's speech, are used to form social bonds with their… (more)

Subjects/Keywords: Paralinguistic; Speech signal processing; Pattern recognition

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APA (6th Edition):

Rao, H. (2015). Paralinguistic event detection in children's speech. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/54332

Chicago Manual of Style (16th Edition):

Rao, Hrishikesh. “Paralinguistic event detection in children's speech.” 2015. Doctoral Dissertation, Georgia Tech. Accessed September 17, 2019. http://hdl.handle.net/1853/54332.

MLA Handbook (7th Edition):

Rao, Hrishikesh. “Paralinguistic event detection in children's speech.” 2015. Web. 17 Sep 2019.

Vancouver:

Rao H. Paralinguistic event detection in children's speech. [Internet] [Doctoral dissertation]. Georgia Tech; 2015. [cited 2019 Sep 17]. Available from: http://hdl.handle.net/1853/54332.

Council of Science Editors:

Rao H. Paralinguistic event detection in children's speech. [Doctoral Dissertation]. Georgia Tech; 2015. Available from: http://hdl.handle.net/1853/54332

9. Matthews, Brett Alexander. Probabilistic modeling of neural data for analysis and synthesis of speech.

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

 This research consists of probabilistic modeling of speech audio signals and deep-brain neurological signals in brain-computer interfaces. A significant portion of this research consists of… (more)

Subjects/Keywords: Neural spike sorting; Automatic speech recognition; Brain-computer interfaces; Machine learning; Digital signal processing; Speech synthesis; Brain-computer interfaces; Neural analyzers

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APA (6th Edition):

Matthews, B. A. (2012). Probabilistic modeling of neural data for analysis and synthesis of speech. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/50116

Chicago Manual of Style (16th Edition):

Matthews, Brett Alexander. “Probabilistic modeling of neural data for analysis and synthesis of speech.” 2012. Doctoral Dissertation, Georgia Tech. Accessed September 17, 2019. http://hdl.handle.net/1853/50116.

MLA Handbook (7th Edition):

Matthews, Brett Alexander. “Probabilistic modeling of neural data for analysis and synthesis of speech.” 2012. Web. 17 Sep 2019.

Vancouver:

Matthews BA. Probabilistic modeling of neural data for analysis and synthesis of speech. [Internet] [Doctoral dissertation]. Georgia Tech; 2012. [cited 2019 Sep 17]. Available from: http://hdl.handle.net/1853/50116.

Council of Science Editors:

Matthews BA. Probabilistic modeling of neural data for analysis and synthesis of speech. [Doctoral Dissertation]. Georgia Tech; 2012. Available from: http://hdl.handle.net/1853/50116

10. Aabed, Mohammed A. Perceptual video quality assessment and analysis using adaptive content dynamics.

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

 With the growth of mobile data services and bandwidth, several applications and streaming services have emerged that made video quality and technologies important fields of… (more)

Subjects/Keywords: Video quality; Perception; Video coding; Distortion; Video streaming; Quality assessment

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APA (6th Edition):

Aabed, M. A. (2017). Perceptual video quality assessment and analysis using adaptive content dynamics. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/58222

Chicago Manual of Style (16th Edition):

Aabed, Mohammed A. “Perceptual video quality assessment and analysis using adaptive content dynamics.” 2017. Doctoral Dissertation, Georgia Tech. Accessed September 17, 2019. http://hdl.handle.net/1853/58222.

MLA Handbook (7th Edition):

Aabed, Mohammed A. “Perceptual video quality assessment and analysis using adaptive content dynamics.” 2017. Web. 17 Sep 2019.

Vancouver:

Aabed MA. Perceptual video quality assessment and analysis using adaptive content dynamics. [Internet] [Doctoral dissertation]. Georgia Tech; 2017. [cited 2019 Sep 17]. Available from: http://hdl.handle.net/1853/58222.

Council of Science Editors:

Aabed MA. Perceptual video quality assessment and analysis using adaptive content dynamics. [Doctoral Dissertation]. Georgia Tech; 2017. Available from: http://hdl.handle.net/1853/58222

11. Zheng, Hao. Prediction and analysis of the methylation status of CpG islands in human genome.

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

 DNA methylation serves as a major epigenetic modification crucial to the normal organismal development and the onset and progression of complex diseases such as cancer.… (more)

Subjects/Keywords: Prediction; Methylation; Epigenetics; DNA Methylation; Genomics Data processing; Bioinformatics

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APA (6th Edition):

Zheng, H. (2012). Prediction and analysis of the methylation status of CpG islands in human genome. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/43631

Chicago Manual of Style (16th Edition):

Zheng, Hao. “Prediction and analysis of the methylation status of CpG islands in human genome.” 2012. Doctoral Dissertation, Georgia Tech. Accessed September 17, 2019. http://hdl.handle.net/1853/43631.

MLA Handbook (7th Edition):

Zheng, Hao. “Prediction and analysis of the methylation status of CpG islands in human genome.” 2012. Web. 17 Sep 2019.

Vancouver:

Zheng H. Prediction and analysis of the methylation status of CpG islands in human genome. [Internet] [Doctoral dissertation]. Georgia Tech; 2012. [cited 2019 Sep 17]. Available from: http://hdl.handle.net/1853/43631.

Council of Science Editors:

Zheng H. Prediction and analysis of the methylation status of CpG islands in human genome. [Doctoral Dissertation]. Georgia Tech; 2012. Available from: http://hdl.handle.net/1853/43631

12. Sun, Rui. The evaluation of the stability of acoustic features in affective conveyance across multiple emotional databases.

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

 The objective of the research presented in this thesis was to systematically investigate the computational structure for cross-database emotion recognition. The research consisted of evaluating… (more)

Subjects/Keywords: Emotion recognition in speech; Cross-database evaluation; Language and emotions; Emotions; Automatic speech recognition; Speech processing systems

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APA (6th Edition):

Sun, R. (2013). The evaluation of the stability of acoustic features in affective conveyance across multiple emotional databases. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/49041

Chicago Manual of Style (16th Edition):

Sun, Rui. “The evaluation of the stability of acoustic features in affective conveyance across multiple emotional databases.” 2013. Doctoral Dissertation, Georgia Tech. Accessed September 17, 2019. http://hdl.handle.net/1853/49041.

MLA Handbook (7th Edition):

Sun, Rui. “The evaluation of the stability of acoustic features in affective conveyance across multiple emotional databases.” 2013. Web. 17 Sep 2019.

Vancouver:

Sun R. The evaluation of the stability of acoustic features in affective conveyance across multiple emotional databases. [Internet] [Doctoral dissertation]. Georgia Tech; 2013. [cited 2019 Sep 17]. Available from: http://hdl.handle.net/1853/49041.

Council of Science Editors:

Sun R. The evaluation of the stability of acoustic features in affective conveyance across multiple emotional databases. [Doctoral Dissertation]. Georgia Tech; 2013. Available from: http://hdl.handle.net/1853/49041

13. 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 17, 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. 17 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 17]. 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

14. Babalola, Karolyn Olatubosun. Brain-computer interfaces for inducing brain plasticity and motor learning: implications for brain-injury rehabilitation.

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

 The goal of this investigation was to explore the efficacy of implementing a rehabilitation robot controlled by a noninvasive brain-computer interface (BCI) to influence brain… (more)

Subjects/Keywords: Guided-imagery; Brain injury; R2; Motor imagery; EEG; Stroke; Motor learning; Brain plasticity; Mu; Beta; Robotic rehabilitation; Rehabilitation; Learning curves; Rate of learning; Beta coherence; SMR; Sensorimotor rhythms; Closed-loop; User interfaces (Computer systems); Brain-computer interfaces; Human-robot interaction; Robotics in medicine; Cerebrovascular disease

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APA (6th Edition):

Babalola, K. O. (2011). Brain-computer interfaces for inducing brain plasticity and motor learning: implications for brain-injury rehabilitation. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/41164

Chicago Manual of Style (16th Edition):

Babalola, Karolyn Olatubosun. “Brain-computer interfaces for inducing brain plasticity and motor learning: implications for brain-injury rehabilitation.” 2011. Doctoral Dissertation, Georgia Tech. Accessed September 17, 2019. http://hdl.handle.net/1853/41164.

MLA Handbook (7th Edition):

Babalola, Karolyn Olatubosun. “Brain-computer interfaces for inducing brain plasticity and motor learning: implications for brain-injury rehabilitation.” 2011. Web. 17 Sep 2019.

Vancouver:

Babalola KO. Brain-computer interfaces for inducing brain plasticity and motor learning: implications for brain-injury rehabilitation. [Internet] [Doctoral dissertation]. Georgia Tech; 2011. [cited 2019 Sep 17]. Available from: http://hdl.handle.net/1853/41164.

Council of Science Editors:

Babalola KO. Brain-computer interfaces for inducing brain plasticity and motor learning: implications for brain-injury rehabilitation. [Doctoral Dissertation]. Georgia Tech; 2011. Available from: http://hdl.handle.net/1853/41164

15. Li, Feng. A methodology for characterizing pavement rutting condition using emerging 3D line laser imaging technology.

Degree: PhD, Civil and Environmental Engineering, 2012, Georgia Tech

 Pavement rutting is one of the major asphalt pavement surface distresses affecting pavement structure integrity and driving safety and is also a required performance measure… (more)

Subjects/Keywords: Pavement condition assessment; Rutting; 3D line laser imaging technology; Pavements; Rutting of roads; Imaging systems; Laser recording

…introduces a sensing vehicle, the Georgia Tech Sensing Vehicle (GTSV), assembled by… 

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APA (6th Edition):

Li, F. (2012). A methodology for characterizing pavement rutting condition using emerging 3D line laser imaging technology. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/50114

Chicago Manual of Style (16th Edition):

Li, Feng. “A methodology for characterizing pavement rutting condition using emerging 3D line laser imaging technology.” 2012. Doctoral Dissertation, Georgia Tech. Accessed September 17, 2019. http://hdl.handle.net/1853/50114.

MLA Handbook (7th Edition):

Li, Feng. “A methodology for characterizing pavement rutting condition using emerging 3D line laser imaging technology.” 2012. Web. 17 Sep 2019.

Vancouver:

Li F. A methodology for characterizing pavement rutting condition using emerging 3D line laser imaging technology. [Internet] [Doctoral dissertation]. Georgia Tech; 2012. [cited 2019 Sep 17]. Available from: http://hdl.handle.net/1853/50114.

Council of Science Editors:

Li F. A methodology for characterizing pavement rutting condition using emerging 3D line laser imaging technology. [Doctoral Dissertation]. Georgia Tech; 2012. Available from: http://hdl.handle.net/1853/50114


Georgia Tech

16. Jeon, Woojay. Speech Analysis and Cognition Using Category-Dependent Features in a Model of the Central Auditory System.

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

 It is well known that machines perform far worse than humans in recognizing speech and audio, especially in noisy environments. One method of addressing this… (more)

Subjects/Keywords: Speech processing; Speech recognition; Feature selection; Pattern recognition; Speech analysis; Auditory model; Auditory cortex; Automatic speech recognition

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APA (6th Edition):

Jeon, W. (2006). Speech Analysis and Cognition Using Category-Dependent Features in a Model of the Central Auditory System. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/14061

Chicago Manual of Style (16th Edition):

Jeon, Woojay. “Speech Analysis and Cognition Using Category-Dependent Features in a Model of the Central Auditory System.” 2006. Doctoral Dissertation, Georgia Tech. Accessed September 17, 2019. http://hdl.handle.net/1853/14061.

MLA Handbook (7th Edition):

Jeon, Woojay. “Speech Analysis and Cognition Using Category-Dependent Features in a Model of the Central Auditory System.” 2006. Web. 17 Sep 2019.

Vancouver:

Jeon W. Speech Analysis and Cognition Using Category-Dependent Features in a Model of the Central Auditory System. [Internet] [Doctoral dissertation]. Georgia Tech; 2006. [cited 2019 Sep 17]. Available from: http://hdl.handle.net/1853/14061.

Council of Science Editors:

Jeon W. Speech Analysis and Cognition Using Category-Dependent Features in a Model of the Central Auditory System. [Doctoral Dissertation]. Georgia Tech; 2006. Available from: http://hdl.handle.net/1853/14061

.