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You searched for +publisher:"Georgia Tech" +contributor:("Romberg, Justin"). Showing records 1 – 30 of 70 total matches.

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Georgia Tech

1. Tanveer, Maham. Classification of anomalous machine sounds using i-vectors.

Degree: MS, Electrical and Computer Engineering, 2020, Georgia Tech

 The objective of the proposed work is to analyze and study the use of i-vectors for Anomalous Detection of Sounds (ADS) in Machines. I-vectors, to… (more)

Subjects/Keywords: I-vector; Anomalous detection of sounds; Machine sounds classification; SVM; Naive Bayes; One-class SVM

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APA (6th Edition):

Tanveer, M. (2020). Classification of anomalous machine sounds using i-vectors. (Masters Thesis). Georgia Tech. Retrieved from http://hdl.handle.net/1853/62812

Chicago Manual of Style (16th Edition):

Tanveer, Maham. “Classification of anomalous machine sounds using i-vectors.” 2020. Masters Thesis, Georgia Tech. Accessed March 07, 2021. http://hdl.handle.net/1853/62812.

MLA Handbook (7th Edition):

Tanveer, Maham. “Classification of anomalous machine sounds using i-vectors.” 2020. Web. 07 Mar 2021.

Vancouver:

Tanveer M. Classification of anomalous machine sounds using i-vectors. [Internet] [Masters thesis]. Georgia Tech; 2020. [cited 2021 Mar 07]. Available from: http://hdl.handle.net/1853/62812.

Council of Science Editors:

Tanveer M. Classification of anomalous machine sounds using i-vectors. [Masters Thesis]. Georgia Tech; 2020. Available from: http://hdl.handle.net/1853/62812


Georgia Tech

2. Vinay, Ashvala. The sound within: Learning audio features from electroencephalogram recordings of music listening.

Degree: MS, Music, 2020, Georgia Tech

 We look at the intersection of music, machine Learning and neuroscience. Specifically, we are interested in understanding how we can predict audio onset events by… (more)

Subjects/Keywords: Music technology; Machine learning; Neuroimaging; EEG; Music information retireval

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APA (6th Edition):

Vinay, A. (2020). The sound within: Learning audio features from electroencephalogram recordings of music listening. (Masters Thesis). Georgia Tech. Retrieved from http://hdl.handle.net/1853/62866

Chicago Manual of Style (16th Edition):

Vinay, Ashvala. “The sound within: Learning audio features from electroencephalogram recordings of music listening.” 2020. Masters Thesis, Georgia Tech. Accessed March 07, 2021. http://hdl.handle.net/1853/62866.

MLA Handbook (7th Edition):

Vinay, Ashvala. “The sound within: Learning audio features from electroencephalogram recordings of music listening.” 2020. Web. 07 Mar 2021.

Vancouver:

Vinay A. The sound within: Learning audio features from electroencephalogram recordings of music listening. [Internet] [Masters thesis]. Georgia Tech; 2020. [cited 2021 Mar 07]. Available from: http://hdl.handle.net/1853/62866.

Council of Science Editors:

Vinay A. The sound within: Learning audio features from electroencephalogram recordings of music listening. [Masters Thesis]. Georgia Tech; 2020. Available from: http://hdl.handle.net/1853/62866


Georgia Tech

3. Witte, Philipp Andre. Software and algorithms for large-scale seismic inverse problems.

Degree: PhD, Computational Science and Engineering, 2020, Georgia Tech

 Seismic imaging and parameter estimation are an import class of inverse problems with practical relevance in resource exploration, carbon control and monitoring systems for geohazards.… (more)

Subjects/Keywords: Seismic; Algorithm; Cloud; High-performance-computing; Geophysics

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APA (6th Edition):

Witte, P. A. (2020). Software and algorithms for large-scale seismic inverse problems. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/62754

Chicago Manual of Style (16th Edition):

Witte, Philipp Andre. “Software and algorithms for large-scale seismic inverse problems.” 2020. Doctoral Dissertation, Georgia Tech. Accessed March 07, 2021. http://hdl.handle.net/1853/62754.

MLA Handbook (7th Edition):

Witte, Philipp Andre. “Software and algorithms for large-scale seismic inverse problems.” 2020. Web. 07 Mar 2021.

Vancouver:

Witte PA. Software and algorithms for large-scale seismic inverse problems. [Internet] [Doctoral dissertation]. Georgia Tech; 2020. [cited 2021 Mar 07]. Available from: http://hdl.handle.net/1853/62754.

Council of Science Editors:

Witte PA. Software and algorithms for large-scale seismic inverse problems. [Doctoral Dissertation]. Georgia Tech; 2020. Available from: http://hdl.handle.net/1853/62754


Georgia Tech

4. McCormick, Jackson C. D region tomography: A technique for ionospheric imaging using lightning-generated sferics and inverse modeling.

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

 The D region of the ionosphere (60-90 km altitude) is a plasma layer which is highly variable on timescales from fractions of a second to… (more)

Subjects/Keywords: D-region; Ionosphere; Lightning; VLF; LF; Sferic; Propagation; Electromagnetics

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APA (6th Edition):

McCormick, J. C. (2019). D region tomography: A technique for ionospheric imaging using lightning-generated sferics and inverse modeling. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/62300

Chicago Manual of Style (16th Edition):

McCormick, Jackson C. “D region tomography: A technique for ionospheric imaging using lightning-generated sferics and inverse modeling.” 2019. Doctoral Dissertation, Georgia Tech. Accessed March 07, 2021. http://hdl.handle.net/1853/62300.

MLA Handbook (7th Edition):

McCormick, Jackson C. “D region tomography: A technique for ionospheric imaging using lightning-generated sferics and inverse modeling.” 2019. Web. 07 Mar 2021.

Vancouver:

McCormick JC. D region tomography: A technique for ionospheric imaging using lightning-generated sferics and inverse modeling. [Internet] [Doctoral dissertation]. Georgia Tech; 2019. [cited 2021 Mar 07]. Available from: http://hdl.handle.net/1853/62300.

Council of Science Editors:

McCormick JC. D region tomography: A technique for ionospheric imaging using lightning-generated sferics and inverse modeling. [Doctoral Dissertation]. Georgia Tech; 2019. Available from: http://hdl.handle.net/1853/62300


Georgia Tech

5. Schnaidt Grez, German Augusto. Non-parametric statistical models using wavelets: Theory and methods.

Degree: PhD, Industrial and Systems Engineering, 2019, Georgia Tech

 Machine Learning and Data Analytics have become key tools in the advancement of modern society, with a vast variety of applications exhibiting exponential growth in… (more)

Subjects/Keywords: Non parametric statistics; Wavelets

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APA (6th Edition):

Schnaidt Grez, G. A. (2019). Non-parametric statistical models using wavelets: Theory and methods. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/62657

Chicago Manual of Style (16th Edition):

Schnaidt Grez, German Augusto. “Non-parametric statistical models using wavelets: Theory and methods.” 2019. Doctoral Dissertation, Georgia Tech. Accessed March 07, 2021. http://hdl.handle.net/1853/62657.

MLA Handbook (7th Edition):

Schnaidt Grez, German Augusto. “Non-parametric statistical models using wavelets: Theory and methods.” 2019. Web. 07 Mar 2021.

Vancouver:

Schnaidt Grez GA. Non-parametric statistical models using wavelets: Theory and methods. [Internet] [Doctoral dissertation]. Georgia Tech; 2019. [cited 2021 Mar 07]. Available from: http://hdl.handle.net/1853/62657.

Council of Science Editors:

Schnaidt Grez GA. Non-parametric statistical models using wavelets: Theory and methods. [Doctoral Dissertation]. Georgia Tech; 2019. Available from: http://hdl.handle.net/1853/62657


Georgia Tech

6. Parihar, Abhinav. Utilizing switched linear dynamics of interconnected state transition devices for approximating certain global functions.

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

 The objective of the proposed research is to create alternative computing models and architectures, unlike (discrete) sequential Turing machine/Von Neumann style models, which utilize the… (more)

Subjects/Keywords: Coupled oscillators; Switched linear dynamics; Eigenvector; Graph coloring

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APA (6th Edition):

Parihar, A. (2019). Utilizing switched linear dynamics of interconnected state transition devices for approximating certain global functions. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/62725

Chicago Manual of Style (16th Edition):

Parihar, Abhinav. “Utilizing switched linear dynamics of interconnected state transition devices for approximating certain global functions.” 2019. Doctoral Dissertation, Georgia Tech. Accessed March 07, 2021. http://hdl.handle.net/1853/62725.

MLA Handbook (7th Edition):

Parihar, Abhinav. “Utilizing switched linear dynamics of interconnected state transition devices for approximating certain global functions.” 2019. Web. 07 Mar 2021.

Vancouver:

Parihar A. Utilizing switched linear dynamics of interconnected state transition devices for approximating certain global functions. [Internet] [Doctoral dissertation]. Georgia Tech; 2019. [cited 2021 Mar 07]. Available from: http://hdl.handle.net/1853/62725.

Council of Science Editors:

Parihar A. Utilizing switched linear dynamics of interconnected state transition devices for approximating certain global functions. [Doctoral Dissertation]. Georgia Tech; 2019. Available from: http://hdl.handle.net/1853/62725


Georgia Tech

7. Amaravati, Anvesha. Energy-efficient circuits and system architectures to enable intelligence at the edge of the cloud.

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

 Internet of Things (IoT) devices are collecting a large amount of data for video processing, monitoring health, etc. Transmitting the data from the sensor to… (more)

Subjects/Keywords: Compressive sensing; Reinforcement learning

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APA (6th Edition):

Amaravati, A. (2018). Energy-efficient circuits and system architectures to enable intelligence at the edge of the cloud. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/62240

Chicago Manual of Style (16th Edition):

Amaravati, Anvesha. “Energy-efficient circuits and system architectures to enable intelligence at the edge of the cloud.” 2018. Doctoral Dissertation, Georgia Tech. Accessed March 07, 2021. http://hdl.handle.net/1853/62240.

MLA Handbook (7th Edition):

Amaravati, Anvesha. “Energy-efficient circuits and system architectures to enable intelligence at the edge of the cloud.” 2018. Web. 07 Mar 2021.

Vancouver:

Amaravati A. Energy-efficient circuits and system architectures to enable intelligence at the edge of the cloud. [Internet] [Doctoral dissertation]. Georgia Tech; 2018. [cited 2021 Mar 07]. Available from: http://hdl.handle.net/1853/62240.

Council of Science Editors:

Amaravati A. Energy-efficient circuits and system architectures to enable intelligence at the edge of the cloud. [Doctoral Dissertation]. Georgia Tech; 2018. Available from: http://hdl.handle.net/1853/62240


Georgia Tech

8. Al-Hussaini, Irfan. Interpretable models for automatic sleep stage scoring.

Degree: MS, Electrical and Computer Engineering, 2020, Georgia Tech

 This thesis aims to combine domain knowledge with deep learning to develop interpretable yet robust models for a particular clinical decision support system, sleep staging.… (more)

Subjects/Keywords: Sleep scoring; Interpretable; Deep learning; CNN; Decision tree; EEG; EOG; EMG

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APA (6th Edition):

Al-Hussaini, I. (2020). Interpretable models for automatic sleep stage scoring. (Masters Thesis). Georgia Tech. Retrieved from http://hdl.handle.net/1853/62851

Chicago Manual of Style (16th Edition):

Al-Hussaini, Irfan. “Interpretable models for automatic sleep stage scoring.” 2020. Masters Thesis, Georgia Tech. Accessed March 07, 2021. http://hdl.handle.net/1853/62851.

MLA Handbook (7th Edition):

Al-Hussaini, Irfan. “Interpretable models for automatic sleep stage scoring.” 2020. Web. 07 Mar 2021.

Vancouver:

Al-Hussaini I. Interpretable models for automatic sleep stage scoring. [Internet] [Masters thesis]. Georgia Tech; 2020. [cited 2021 Mar 07]. Available from: http://hdl.handle.net/1853/62851.

Council of Science Editors:

Al-Hussaini I. Interpretable models for automatic sleep stage scoring. [Masters Thesis]. Georgia Tech; 2020. Available from: http://hdl.handle.net/1853/62851


Georgia Tech

9. Xu, Shaojie. Machine Learning Algorithm Design for Hardware Performance Optimization.

Degree: PhD, Electrical and Computer Engineering, 2020, Georgia Tech

 Machine learning has enabled us to extract and exploit information from collected data. In this thesis, we are particularly interested in how we can apply… (more)

Subjects/Keywords: Machine Learning; Algorithm-Hardware; Co-Design; Control; Compressive Sensing; Bandits; Reinforcement Learning

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APA (6th Edition):

Xu, S. (2020). Machine Learning Algorithm Design for Hardware Performance Optimization. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/62794

Chicago Manual of Style (16th Edition):

Xu, Shaojie. “Machine Learning Algorithm Design for Hardware Performance Optimization.” 2020. Doctoral Dissertation, Georgia Tech. Accessed March 07, 2021. http://hdl.handle.net/1853/62794.

MLA Handbook (7th Edition):

Xu, Shaojie. “Machine Learning Algorithm Design for Hardware Performance Optimization.” 2020. Web. 07 Mar 2021.

Vancouver:

Xu S. Machine Learning Algorithm Design for Hardware Performance Optimization. [Internet] [Doctoral dissertation]. Georgia Tech; 2020. [cited 2021 Mar 07]. Available from: http://hdl.handle.net/1853/62794.

Council of Science Editors:

Xu S. Machine Learning Algorithm Design for Hardware Performance Optimization. [Doctoral Dissertation]. Georgia Tech; 2020. Available from: http://hdl.handle.net/1853/62794


Georgia Tech

10. Shih, Ping-Chang. Joint variational camera calibration refinement and 4-D stereo reconstruction applied to oceanic sea states.

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

 In this thesis, an innovative algorithm for improving the accuracy of variational space-time stereoscopic reconstruction of ocean surfaces is presented. The space-time reconstruction method, developed… (more)

Subjects/Keywords: Stereo computer vision; Camera calibration; 3-D reconstruction; Variational

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APA (6th Edition):

Shih, P. (2014). Joint variational camera calibration refinement and 4-D stereo reconstruction applied to oceanic sea states. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/52320

Chicago Manual of Style (16th Edition):

Shih, Ping-Chang. “Joint variational camera calibration refinement and 4-D stereo reconstruction applied to oceanic sea states.” 2014. Doctoral Dissertation, Georgia Tech. Accessed March 07, 2021. http://hdl.handle.net/1853/52320.

MLA Handbook (7th Edition):

Shih, Ping-Chang. “Joint variational camera calibration refinement and 4-D stereo reconstruction applied to oceanic sea states.” 2014. Web. 07 Mar 2021.

Vancouver:

Shih P. Joint variational camera calibration refinement and 4-D stereo reconstruction applied to oceanic sea states. [Internet] [Doctoral dissertation]. Georgia Tech; 2014. [cited 2021 Mar 07]. Available from: http://hdl.handle.net/1853/52320.

Council of Science Editors:

Shih P. Joint variational camera calibration refinement and 4-D stereo reconstruction applied to oceanic sea states. [Doctoral Dissertation]. Georgia Tech; 2014. Available from: http://hdl.handle.net/1853/52320


Georgia Tech

11. Luo, Chenchi. Non-uniform sampling: algorithms and architectures.

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

 Modern signal processing applications emerging in telecommunication and instrumentation industries have placed an increasing demand for ADCs with higher speed and resolution. The most fundamental… (more)

Subjects/Keywords: TIADC; Farrow structure; Compressive sensing; Sparsity; Analog-to-digital converters; Sampling (Statistics); Algorithms; Signal processing; Signal processing Digital techniques

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APA (6th Edition):

Luo, C. (2012). Non-uniform sampling: algorithms and architectures. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/45873

Chicago Manual of Style (16th Edition):

Luo, Chenchi. “Non-uniform sampling: algorithms and architectures.” 2012. Doctoral Dissertation, Georgia Tech. Accessed March 07, 2021. http://hdl.handle.net/1853/45873.

MLA Handbook (7th Edition):

Luo, Chenchi. “Non-uniform sampling: algorithms and architectures.” 2012. Web. 07 Mar 2021.

Vancouver:

Luo C. Non-uniform sampling: algorithms and architectures. [Internet] [Doctoral dissertation]. Georgia Tech; 2012. [cited 2021 Mar 07]. Available from: http://hdl.handle.net/1853/45873.

Council of Science Editors:

Luo C. Non-uniform sampling: algorithms and architectures. [Doctoral Dissertation]. Georgia Tech; 2012. Available from: http://hdl.handle.net/1853/45873


Georgia Tech

12. Nichols, Brendan. Exploiting ambient noise for coherent processing of mobile vector sensor arrays.

Degree: PhD, Mechanical Engineering, 2018, Georgia Tech

 A network of mobile sensors, such as vector sensors mounted to drifting floats, can be used as an array for locating acoustic sources in an… (more)

Subjects/Keywords: Ambient noise; Coherent processing; Beamforming; Vector sensor; Array signal processing; Stochastic search; Experimental data; Noise correlation

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APA (6th Edition):

Nichols, B. (2018). Exploiting ambient noise for coherent processing of mobile vector sensor arrays. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/59897

Chicago Manual of Style (16th Edition):

Nichols, Brendan. “Exploiting ambient noise for coherent processing of mobile vector sensor arrays.” 2018. Doctoral Dissertation, Georgia Tech. Accessed March 07, 2021. http://hdl.handle.net/1853/59897.

MLA Handbook (7th Edition):

Nichols, Brendan. “Exploiting ambient noise for coherent processing of mobile vector sensor arrays.” 2018. Web. 07 Mar 2021.

Vancouver:

Nichols B. Exploiting ambient noise for coherent processing of mobile vector sensor arrays. [Internet] [Doctoral dissertation]. Georgia Tech; 2018. [cited 2021 Mar 07]. Available from: http://hdl.handle.net/1853/59897.

Council of Science Editors:

Nichols B. Exploiting ambient noise for coherent processing of mobile vector sensor arrays. [Doctoral Dissertation]. Georgia Tech; 2018. Available from: http://hdl.handle.net/1853/59897


Georgia Tech

13. Whitaker, Bradley M. Modifying sparse coding to model imbalanced datasets.

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

 The objective of this research is to explore the use of sparse coding as a tool for unsupervised feature learning to more effectively model imbalanced… (more)

Subjects/Keywords: Sparse coding; Imbalanced data; Machine learning

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APA (6th Edition):

Whitaker, B. M. (2018). Modifying sparse coding to model imbalanced datasets. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/59919

Chicago Manual of Style (16th Edition):

Whitaker, Bradley M. “Modifying sparse coding to model imbalanced datasets.” 2018. Doctoral Dissertation, Georgia Tech. Accessed March 07, 2021. http://hdl.handle.net/1853/59919.

MLA Handbook (7th Edition):

Whitaker, Bradley M. “Modifying sparse coding to model imbalanced datasets.” 2018. Web. 07 Mar 2021.

Vancouver:

Whitaker BM. Modifying sparse coding to model imbalanced datasets. [Internet] [Doctoral dissertation]. Georgia Tech; 2018. [cited 2021 Mar 07]. Available from: http://hdl.handle.net/1853/59919.

Council of Science Editors:

Whitaker BM. Modifying sparse coding to model imbalanced datasets. [Doctoral Dissertation]. Georgia Tech; 2018. Available from: http://hdl.handle.net/1853/59919


Georgia Tech

14. Zafar, Munzir. Whole body control of wheeled inverted pendulum humanoids.

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

 A framework for controlling a Wheeled Inverted Pendulum (WIP) Humanoid to perform useful interactions with the environment, while dynamically balancing itself on two wheels, was… (more)

Subjects/Keywords: Whole body control; Wheeled inverted pendulum; Humanoids; Hierarchical; Optimization; Operational space; Model predictive control

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APA (6th Edition):

Zafar, M. (2019). Whole body control of wheeled inverted pendulum humanoids. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/61739

Chicago Manual of Style (16th Edition):

Zafar, Munzir. “Whole body control of wheeled inverted pendulum humanoids.” 2019. Doctoral Dissertation, Georgia Tech. Accessed March 07, 2021. http://hdl.handle.net/1853/61739.

MLA Handbook (7th Edition):

Zafar, Munzir. “Whole body control of wheeled inverted pendulum humanoids.” 2019. Web. 07 Mar 2021.

Vancouver:

Zafar M. Whole body control of wheeled inverted pendulum humanoids. [Internet] [Doctoral dissertation]. Georgia Tech; 2019. [cited 2021 Mar 07]. Available from: http://hdl.handle.net/1853/61739.

Council of Science Editors:

Zafar M. Whole body control of wheeled inverted pendulum humanoids. [Doctoral Dissertation]. Georgia Tech; 2019. Available from: http://hdl.handle.net/1853/61739


Georgia Tech

15. Xia, Dong. Statistical inference for large matrices.

Degree: PhD, Mathematics, 2016, Georgia Tech

 This thesis covers two topics on matrix analysis and estimation in machine learning and statistics. The first topic is about density matrix estimation with application… (more)

Subjects/Keywords: Low rank; Matrix estimation; Singular vectors; Random perturbation

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APA (6th Edition):

Xia, D. (2016). Statistical inference for large matrices. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/55632

Chicago Manual of Style (16th Edition):

Xia, Dong. “Statistical inference for large matrices.” 2016. Doctoral Dissertation, Georgia Tech. Accessed March 07, 2021. http://hdl.handle.net/1853/55632.

MLA Handbook (7th Edition):

Xia, Dong. “Statistical inference for large matrices.” 2016. Web. 07 Mar 2021.

Vancouver:

Xia D. Statistical inference for large matrices. [Internet] [Doctoral dissertation]. Georgia Tech; 2016. [cited 2021 Mar 07]. Available from: http://hdl.handle.net/1853/55632.

Council of Science Editors:

Xia D. Statistical inference for large matrices. [Doctoral Dissertation]. Georgia Tech; 2016. Available from: http://hdl.handle.net/1853/55632


Georgia Tech

16. Abdi, Afshin. Distributed learning and inference in deep models.

Degree: PhD, Electrical and Computer Engineering, 2020, Georgia Tech

 In recent years, the size of deep learning problems has been increased significantly, both in terms of the number of available training samples as well… (more)

Subjects/Keywords: Machine learning; Artificial intelligence; Distributed training; Distributed learning

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APA (6th Edition):

Abdi, A. (2020). Distributed learning and inference in deep models. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/63671

Chicago Manual of Style (16th Edition):

Abdi, Afshin. “Distributed learning and inference in deep models.” 2020. Doctoral Dissertation, Georgia Tech. Accessed March 07, 2021. http://hdl.handle.net/1853/63671.

MLA Handbook (7th Edition):

Abdi, Afshin. “Distributed learning and inference in deep models.” 2020. Web. 07 Mar 2021.

Vancouver:

Abdi A. Distributed learning and inference in deep models. [Internet] [Doctoral dissertation]. Georgia Tech; 2020. [cited 2021 Mar 07]. Available from: http://hdl.handle.net/1853/63671.

Council of Science Editors:

Abdi A. Distributed learning and inference in deep models. [Doctoral Dissertation]. Georgia Tech; 2020. Available from: http://hdl.handle.net/1853/63671


Georgia Tech

17. Lee, John Zhan Yi. Exploiting Low-dimensional Structure and Optimal Transport for Tracking and Alignment.

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

 The objective of this thesis is to exploit low-dimensional structures (e.g., sparsity, low-rankness) and optimal transport theory to develop new tools for inference and distribution… (more)

Subjects/Keywords: inverse problems; optimal transport; tracking; distribution alignment; optimization

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APA (6th Edition):

Lee, J. Z. Y. (2019). Exploiting Low-dimensional Structure and Optimal Transport for Tracking and Alignment. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/64011

Chicago Manual of Style (16th Edition):

Lee, John Zhan Yi. “Exploiting Low-dimensional Structure and Optimal Transport for Tracking and Alignment.” 2019. Doctoral Dissertation, Georgia Tech. Accessed March 07, 2021. http://hdl.handle.net/1853/64011.

MLA Handbook (7th Edition):

Lee, John Zhan Yi. “Exploiting Low-dimensional Structure and Optimal Transport for Tracking and Alignment.” 2019. Web. 07 Mar 2021.

Vancouver:

Lee JZY. Exploiting Low-dimensional Structure and Optimal Transport for Tracking and Alignment. [Internet] [Doctoral dissertation]. Georgia Tech; 2019. [cited 2021 Mar 07]. Available from: http://hdl.handle.net/1853/64011.

Council of Science Editors:

Lee JZY. Exploiting Low-dimensional Structure and Optimal Transport for Tracking and Alignment. [Doctoral Dissertation]. Georgia Tech; 2019. Available from: http://hdl.handle.net/1853/64011


Georgia Tech

18. Friedlander, Robert Daniel. Thin Lens-Based Geometric Surface Inversion for Multiview Stereo.

Degree: PhD, Electrical and Computer Engineering, 2020, Georgia Tech

 Current state-of-the-art multiview reconstruction methods are founded on a pinhole camera model that assumes perfectly focused images and thus fail when given defocused image data.… (more)

Subjects/Keywords: Multiview reconstruction; Variational methods; Thin lens model; Image irradiance

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APA (6th Edition):

Friedlander, R. D. (2020). Thin Lens-Based Geometric Surface Inversion for Multiview Stereo. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/64140

Chicago Manual of Style (16th Edition):

Friedlander, Robert Daniel. “Thin Lens-Based Geometric Surface Inversion for Multiview Stereo.” 2020. Doctoral Dissertation, Georgia Tech. Accessed March 07, 2021. http://hdl.handle.net/1853/64140.

MLA Handbook (7th Edition):

Friedlander, Robert Daniel. “Thin Lens-Based Geometric Surface Inversion for Multiview Stereo.” 2020. Web. 07 Mar 2021.

Vancouver:

Friedlander RD. Thin Lens-Based Geometric Surface Inversion for Multiview Stereo. [Internet] [Doctoral dissertation]. Georgia Tech; 2020. [cited 2021 Mar 07]. Available from: http://hdl.handle.net/1853/64140.

Council of Science Editors:

Friedlander RD. Thin Lens-Based Geometric Surface Inversion for Multiview Stereo. [Doctoral Dissertation]. Georgia Tech; 2020. Available from: http://hdl.handle.net/1853/64140


Georgia Tech

19. Srinivasa, Rakshith. Subspace learning by randomized sketching.

Degree: PhD, Electrical and Computer Engineering, 2020, Georgia Tech

 High dimensional data is often accompanied by inherent low dimensionality that can be leveraged to design scalable machine learning and signal processing algorithms. Developing efficient… (more)

Subjects/Keywords: Subspace learning; randomized numerical linear algebra; array processing; sketching

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APA (6th Edition):

Srinivasa, R. (2020). Subspace learning by randomized sketching. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/64177

Chicago Manual of Style (16th Edition):

Srinivasa, Rakshith. “Subspace learning by randomized sketching.” 2020. Doctoral Dissertation, Georgia Tech. Accessed March 07, 2021. http://hdl.handle.net/1853/64177.

MLA Handbook (7th Edition):

Srinivasa, Rakshith. “Subspace learning by randomized sketching.” 2020. Web. 07 Mar 2021.

Vancouver:

Srinivasa R. Subspace learning by randomized sketching. [Internet] [Doctoral dissertation]. Georgia Tech; 2020. [cited 2021 Mar 07]. Available from: http://hdl.handle.net/1853/64177.

Council of Science Editors:

Srinivasa R. Subspace learning by randomized sketching. [Doctoral Dissertation]. Georgia Tech; 2020. Available from: http://hdl.handle.net/1853/64177

20. Shaban, Fahad. Application of L1 reconstruction of sparse signals to ambiguity resolution in radar.

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

 The objective of the proposed research is to develop a new algorithm for range and Doppler ambiguity resolution in radar detection data using L1 minimization… (more)

Subjects/Keywords: Ambiguity resolution; Pulse Doppler radars; Sparse reconstruction; Multiple PRFs; L1 minimization; Radar; Signal detection; Sparse matrices

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APA (6th Edition):

Shaban, F. (2013). Application of L1 reconstruction of sparse signals to ambiguity resolution in radar. (Masters Thesis). Georgia Tech. Retrieved from http://hdl.handle.net/1853/47637

Chicago Manual of Style (16th Edition):

Shaban, Fahad. “Application of L1 reconstruction of sparse signals to ambiguity resolution in radar.” 2013. Masters Thesis, Georgia Tech. Accessed March 07, 2021. http://hdl.handle.net/1853/47637.

MLA Handbook (7th Edition):

Shaban, Fahad. “Application of L1 reconstruction of sparse signals to ambiguity resolution in radar.” 2013. Web. 07 Mar 2021.

Vancouver:

Shaban F. Application of L1 reconstruction of sparse signals to ambiguity resolution in radar. [Internet] [Masters thesis]. Georgia Tech; 2013. [cited 2021 Mar 07]. Available from: http://hdl.handle.net/1853/47637.

Council of Science Editors:

Shaban F. Application of L1 reconstruction of sparse signals to ambiguity resolution in radar. [Masters Thesis]. Georgia Tech; 2013. Available from: http://hdl.handle.net/1853/47637

21. Colón, Guillermo J. Avian musing feature space analysis.

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

 The purpose of this study was to analyze the possibility of utilizing known signal processing and machine learning algorithms to correlate environmental data to chicken… (more)

Subjects/Keywords: Broiler; Chicken; Feature; Audio; Segmentation; Signal processing Digital techniques; Machine learning; Sound production by animals; Chickens Vocalization

Page 1 Page 2 Page 3 Page 4 Page 5 Page 6 Page 7 Sample image

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APA (6th Edition):

Colón, G. J. (2012). Avian musing feature space analysis. (Masters Thesis). Georgia Tech. Retrieved from http://hdl.handle.net/1853/44754

Chicago Manual of Style (16th Edition):

Colón, Guillermo J. “Avian musing feature space analysis.” 2012. Masters Thesis, Georgia Tech. Accessed March 07, 2021. http://hdl.handle.net/1853/44754.

MLA Handbook (7th Edition):

Colón, Guillermo J. “Avian musing feature space analysis.” 2012. Web. 07 Mar 2021.

Vancouver:

Colón GJ. Avian musing feature space analysis. [Internet] [Masters thesis]. Georgia Tech; 2012. [cited 2021 Mar 07]. Available from: http://hdl.handle.net/1853/44754.

Council of Science Editors:

Colón GJ. Avian musing feature space analysis. [Masters Thesis]. Georgia Tech; 2012. Available from: http://hdl.handle.net/1853/44754

22. Lani, Shane W. Passive acoustic imaging and monitoring using ambient noise.

Degree: MS, Mechanical Engineering, 2012, Georgia Tech

 An approximate of the Green's function can be obtained by taking the cross-correlation of ambient noise that has been simultaneously recorded on separate sensors. This… (more)

Subjects/Keywords: Ultrasound imaging; Noise imaging; Ocean monitoring; Noise; Cross-correlation; Noise monitoring; Ambient sounds; Green's functions

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APA (6th Edition):

Lani, S. W. (2012). Passive acoustic imaging and monitoring using ambient noise. (Masters Thesis). Georgia Tech. Retrieved from http://hdl.handle.net/1853/50136

Chicago Manual of Style (16th Edition):

Lani, Shane W. “Passive acoustic imaging and monitoring using ambient noise.” 2012. Masters Thesis, Georgia Tech. Accessed March 07, 2021. http://hdl.handle.net/1853/50136.

MLA Handbook (7th Edition):

Lani, Shane W. “Passive acoustic imaging and monitoring using ambient noise.” 2012. Web. 07 Mar 2021.

Vancouver:

Lani SW. Passive acoustic imaging and monitoring using ambient noise. [Internet] [Masters thesis]. Georgia Tech; 2012. [cited 2021 Mar 07]. Available from: http://hdl.handle.net/1853/50136.

Council of Science Editors:

Lani SW. Passive acoustic imaging and monitoring using ambient noise. [Masters Thesis]. Georgia Tech; 2012. Available from: http://hdl.handle.net/1853/50136

23. Somoye, Idris Olansile. GPU accelerated adaptive compressed sensing.

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

 There are presently image sensors based around compressed sensing that apply the fundamental theory to video acquisition; however, these imagers require specialized hardware modules that… (more)

Subjects/Keywords: GPU; Compressed sensing; GPGPU; Predictive video encoding

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APA (6th Edition):

Somoye, I. O. (2016). GPU accelerated adaptive compressed sensing. (Masters Thesis). Georgia Tech. Retrieved from http://hdl.handle.net/1853/56379

Chicago Manual of Style (16th Edition):

Somoye, Idris Olansile. “GPU accelerated adaptive compressed sensing.” 2016. Masters Thesis, Georgia Tech. Accessed March 07, 2021. http://hdl.handle.net/1853/56379.

MLA Handbook (7th Edition):

Somoye, Idris Olansile. “GPU accelerated adaptive compressed sensing.” 2016. Web. 07 Mar 2021.

Vancouver:

Somoye IO. GPU accelerated adaptive compressed sensing. [Internet] [Masters thesis]. Georgia Tech; 2016. [cited 2021 Mar 07]. Available from: http://hdl.handle.net/1853/56379.

Council of Science Editors:

Somoye IO. GPU accelerated adaptive compressed sensing. [Masters Thesis]. Georgia Tech; 2016. Available from: http://hdl.handle.net/1853/56379

24. Wong, Lok S. Optimal partitions for the fast multipole method.

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

 The fast multipole method is an algorithm first developed to approximately solve the N-body problem in linear time. Part of the FMM involves recursively partitioning… (more)

Subjects/Keywords: Fast multipole method; Partition

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APA (6th Edition):

Wong, L. S. (2016). Optimal partitions for the fast multipole method. (Masters Thesis). Georgia Tech. Retrieved from http://hdl.handle.net/1853/56360

Chicago Manual of Style (16th Edition):

Wong, Lok S. “Optimal partitions for the fast multipole method.” 2016. Masters Thesis, Georgia Tech. Accessed March 07, 2021. http://hdl.handle.net/1853/56360.

MLA Handbook (7th Edition):

Wong, Lok S. “Optimal partitions for the fast multipole method.” 2016. Web. 07 Mar 2021.

Vancouver:

Wong LS. Optimal partitions for the fast multipole method. [Internet] [Masters thesis]. Georgia Tech; 2016. [cited 2021 Mar 07]. Available from: http://hdl.handle.net/1853/56360.

Council of Science Editors:

Wong LS. Optimal partitions for the fast multipole method. [Masters Thesis]. Georgia Tech; 2016. Available from: http://hdl.handle.net/1853/56360

25. Kagie, Matthew Joseph. Time-of-arrival estimation for saturated optical transients using censored probabilistic models.

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

 The objective of the proposed research is to estimate the time-of-arrival of a transient optical signal subjected to a particular type of nonlinear distortion. The… (more)

Subjects/Keywords: Expectation maximization algorithms; Poisson models; Cramér-Rao bounds; Lightning; Machine learning

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APA (6th Edition):

Kagie, M. J. (2016). Time-of-arrival estimation for saturated optical transients using censored probabilistic models. (Masters Thesis). Georgia Tech. Retrieved from http://hdl.handle.net/1853/56365

Chicago Manual of Style (16th Edition):

Kagie, Matthew Joseph. “Time-of-arrival estimation for saturated optical transients using censored probabilistic models.” 2016. Masters Thesis, Georgia Tech. Accessed March 07, 2021. http://hdl.handle.net/1853/56365.

MLA Handbook (7th Edition):

Kagie, Matthew Joseph. “Time-of-arrival estimation for saturated optical transients using censored probabilistic models.” 2016. Web. 07 Mar 2021.

Vancouver:

Kagie MJ. Time-of-arrival estimation for saturated optical transients using censored probabilistic models. [Internet] [Masters thesis]. Georgia Tech; 2016. [cited 2021 Mar 07]. Available from: http://hdl.handle.net/1853/56365.

Council of Science Editors:

Kagie MJ. Time-of-arrival estimation for saturated optical transients using censored probabilistic models. [Masters Thesis]. Georgia Tech; 2016. Available from: http://hdl.handle.net/1853/56365

26. Tan, Edward S. Hyper-wideband OFDM system.

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

 Hyper-wideband communications represent the next frontier in spread spectrum RF systems with an excess of 10 GHz instantaneous bandwidth. In this thesis, an end-to-end physical… (more)

Subjects/Keywords: OFDM; Support vector regression; Hyper-wideband

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APA (6th Edition):

Tan, E. S. (2016). Hyper-wideband OFDM system. (Masters Thesis). Georgia Tech. Retrieved from http://hdl.handle.net/1853/55056

Chicago Manual of Style (16th Edition):

Tan, Edward S. “Hyper-wideband OFDM system.” 2016. Masters Thesis, Georgia Tech. Accessed March 07, 2021. http://hdl.handle.net/1853/55056.

MLA Handbook (7th Edition):

Tan, Edward S. “Hyper-wideband OFDM system.” 2016. Web. 07 Mar 2021.

Vancouver:

Tan ES. Hyper-wideband OFDM system. [Internet] [Masters thesis]. Georgia Tech; 2016. [cited 2021 Mar 07]. Available from: http://hdl.handle.net/1853/55056.

Council of Science Editors:

Tan ES. Hyper-wideband OFDM system. [Masters Thesis]. Georgia Tech; 2016. Available from: http://hdl.handle.net/1853/55056


Georgia Tech

27. Bales, Michael Ryan. Illumination compensation in video surveillance analysis.

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

 Problems in automated video surveillance analysis caused by illumination changes are explored, and solutions are presented. Controlled experiments are first conducted to measure the responses… (more)

Subjects/Keywords: Tracking; Color; Computer vision; Background model; BigBackground; Illumination change; Video surveillance; Lighting; Video recording Lighting

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APA (6th Edition):

Bales, M. R. (2011). Illumination compensation in video surveillance analysis. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/39535

Chicago Manual of Style (16th Edition):

Bales, Michael Ryan. “Illumination compensation in video surveillance analysis.” 2011. Doctoral Dissertation, Georgia Tech. Accessed March 07, 2021. http://hdl.handle.net/1853/39535.

MLA Handbook (7th Edition):

Bales, Michael Ryan. “Illumination compensation in video surveillance analysis.” 2011. Web. 07 Mar 2021.

Vancouver:

Bales MR. Illumination compensation in video surveillance analysis. [Internet] [Doctoral dissertation]. Georgia Tech; 2011. [cited 2021 Mar 07]. Available from: http://hdl.handle.net/1853/39535.

Council of Science Editors:

Bales MR. Illumination compensation in video surveillance analysis. [Doctoral Dissertation]. Georgia Tech; 2011. Available from: http://hdl.handle.net/1853/39535


Georgia Tech

28. Chang, Muya. Hardware Dynamical System for Solving Optimization Problems.

Degree: PhD, Electrical and Computer Engineering, 2020, Georgia Tech

 Optimization problems form the basis of a wide gamut of computationally challenging tasks in signal processing, machine learning, resource planning and so on. Out of… (more)

Subjects/Keywords: Optimization; Signal processing algorithms; Distributed databases; Computational modeling; Training; Convex functions; Hardware

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APA (6th Edition):

Chang, M. (2020). Hardware Dynamical System for Solving Optimization Problems. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/64104

Chicago Manual of Style (16th Edition):

Chang, Muya. “Hardware Dynamical System for Solving Optimization Problems.” 2020. Doctoral Dissertation, Georgia Tech. Accessed March 07, 2021. http://hdl.handle.net/1853/64104.

MLA Handbook (7th Edition):

Chang, Muya. “Hardware Dynamical System for Solving Optimization Problems.” 2020. Web. 07 Mar 2021.

Vancouver:

Chang M. Hardware Dynamical System for Solving Optimization Problems. [Internet] [Doctoral dissertation]. Georgia Tech; 2020. [cited 2021 Mar 07]. Available from: http://hdl.handle.net/1853/64104.

Council of Science Editors:

Chang M. Hardware Dynamical System for Solving Optimization Problems. [Doctoral Dissertation]. Georgia Tech; 2020. Available from: http://hdl.handle.net/1853/64104

29. Remenyi, Norbert. Contributions to Bayesian wavelet shrinkage.

Degree: PhD, Industrial and Systems Engineering, 2012, Georgia Tech

 This thesis provides contributions to research in Bayesian modeling and shrinkage in the wavelet domain. Wavelets are a powerful tool to describe phenomena rapidly changing… (more)

Subjects/Keywords: Bayes factor; Bayesian estimation; Bayesian infere; Wavelets (Mathematics); Bayesian statistical decision theory; Mathematical statistics

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APA (6th Edition):

Remenyi, N. (2012). Contributions to Bayesian wavelet shrinkage. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/45898

Chicago Manual of Style (16th Edition):

Remenyi, Norbert. “Contributions to Bayesian wavelet shrinkage.” 2012. Doctoral Dissertation, Georgia Tech. Accessed March 07, 2021. http://hdl.handle.net/1853/45898.

MLA Handbook (7th Edition):

Remenyi, Norbert. “Contributions to Bayesian wavelet shrinkage.” 2012. Web. 07 Mar 2021.

Vancouver:

Remenyi N. Contributions to Bayesian wavelet shrinkage. [Internet] [Doctoral dissertation]. Georgia Tech; 2012. [cited 2021 Mar 07]. Available from: http://hdl.handle.net/1853/45898.

Council of Science Editors:

Remenyi N. Contributions to Bayesian wavelet shrinkage. [Doctoral Dissertation]. Georgia Tech; 2012. Available from: http://hdl.handle.net/1853/45898

30. Sconyers, Christopher. Particle filter-based architecture for video target tracking and geo-location using multiple UAVs.

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

 Research in the areas of target detection, tracking, and geo-location is most important for enabling an unmanned aerial vehicle (UAV) platform to autonomously execute a… (more)

Subjects/Keywords: Rotorcraft; Localization; Monte Carlo; Particle filter; Multi-modal; State space; Observer; Gimbal; Markov; Drone aircraft; Target acquisition

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APA (6th Edition):

Sconyers, C. (2013). Particle filter-based architecture for video target tracking and geo-location using multiple UAVs. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/47734

Chicago Manual of Style (16th Edition):

Sconyers, Christopher. “Particle filter-based architecture for video target tracking and geo-location using multiple UAVs.” 2013. Doctoral Dissertation, Georgia Tech. Accessed March 07, 2021. http://hdl.handle.net/1853/47734.

MLA Handbook (7th Edition):

Sconyers, Christopher. “Particle filter-based architecture for video target tracking and geo-location using multiple UAVs.” 2013. Web. 07 Mar 2021.

Vancouver:

Sconyers C. Particle filter-based architecture for video target tracking and geo-location using multiple UAVs. [Internet] [Doctoral dissertation]. Georgia Tech; 2013. [cited 2021 Mar 07]. Available from: http://hdl.handle.net/1853/47734.

Council of Science Editors:

Sconyers C. Particle filter-based architecture for video target tracking and geo-location using multiple UAVs. [Doctoral Dissertation]. Georgia Tech; 2013. Available from: http://hdl.handle.net/1853/47734

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