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You searched for +publisher:"Georgia Tech" +contributor:("Anderson, David"). Showing records 1 – 30 of 128 total matches.

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Georgia Tech

1. Yang, Yufeng. Automatic speaker verification and diarization on VoxCeleb data collection.

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

 Automatic speaker verification (ASV) is increasingly getting more attention in speech research field in recent years. Because of the importance of cyber-security and personal property… (more)

Subjects/Keywords: Automatic speaker verification; Speaker diarization; Dataset; VoxCeleb

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APA (6th Edition):

Yang, Y. (2020). Automatic speaker verification and diarization on VoxCeleb data collection. (Masters Thesis). Georgia Tech. Retrieved from http://hdl.handle.net/1853/62830

Chicago Manual of Style (16th Edition):

Yang, Yufeng. “Automatic speaker verification and diarization on VoxCeleb data collection.” 2020. Masters Thesis, Georgia Tech. Accessed October 01, 2020. http://hdl.handle.net/1853/62830.

MLA Handbook (7th Edition):

Yang, Yufeng. “Automatic speaker verification and diarization on VoxCeleb data collection.” 2020. Web. 01 Oct 2020.

Vancouver:

Yang Y. Automatic speaker verification and diarization on VoxCeleb data collection. [Internet] [Masters thesis]. Georgia Tech; 2020. [cited 2020 Oct 01]. Available from: http://hdl.handle.net/1853/62830.

Council of Science Editors:

Yang Y. Automatic speaker verification and diarization on VoxCeleb data collection. [Masters Thesis]. Georgia Tech; 2020. Available from: http://hdl.handle.net/1853/62830


Georgia Tech

2. 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 October 01, 2020. http://hdl.handle.net/1853/62812.

MLA Handbook (7th Edition):

Tanveer, Maham. “Classification of anomalous machine sounds using i-vectors.” 2020. Web. 01 Oct 2020.

Vancouver:

Tanveer M. Classification of anomalous machine sounds using i-vectors. [Internet] [Masters thesis]. Georgia Tech; 2020. [cited 2020 Oct 01]. 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

3. Venkataramanan, Aishwarya. Generation of realistic tree barks using deep learning.

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

 With the increase in demand for high-quality visual content in video games, movies, and simulators, it is of paramount importance to create realistic 3D models… (more)

Subjects/Keywords: Tree modeling; Generative adversarial networks

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APA (6th Edition):

Venkataramanan, A. (2020). Generation of realistic tree barks using deep learning. (Masters Thesis). Georgia Tech. Retrieved from http://hdl.handle.net/1853/62856

Chicago Manual of Style (16th Edition):

Venkataramanan, Aishwarya. “Generation of realistic tree barks using deep learning.” 2020. Masters Thesis, Georgia Tech. Accessed October 01, 2020. http://hdl.handle.net/1853/62856.

MLA Handbook (7th Edition):

Venkataramanan, Aishwarya. “Generation of realistic tree barks using deep learning.” 2020. Web. 01 Oct 2020.

Vancouver:

Venkataramanan A. Generation of realistic tree barks using deep learning. [Internet] [Masters thesis]. Georgia Tech; 2020. [cited 2020 Oct 01]. Available from: http://hdl.handle.net/1853/62856.

Council of Science Editors:

Venkataramanan A. Generation of realistic tree barks using deep learning. [Masters Thesis]. Georgia Tech; 2020. Available from: http://hdl.handle.net/1853/62856


Georgia Tech

4. Haresamudram, Harish. The role of representations in human activity recognition.

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

 We investigate the role of representations in sensor based human activity recognition (HAR). In particular, we develop convolutional and recurrent autoencoder architectures for feature learning… (more)

Subjects/Keywords: Unsupervised learning; Human activity recognition; Autoencoder models

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APA (6th Edition):

Haresamudram, H. (2019). The role of representations in human activity recognition. (Masters Thesis). Georgia Tech. Retrieved from http://hdl.handle.net/1853/62706

Chicago Manual of Style (16th Edition):

Haresamudram, Harish. “The role of representations in human activity recognition.” 2019. Masters Thesis, Georgia Tech. Accessed October 01, 2020. http://hdl.handle.net/1853/62706.

MLA Handbook (7th Edition):

Haresamudram, Harish. “The role of representations in human activity recognition.” 2019. Web. 01 Oct 2020.

Vancouver:

Haresamudram H. The role of representations in human activity recognition. [Internet] [Masters thesis]. Georgia Tech; 2019. [cited 2020 Oct 01]. Available from: http://hdl.handle.net/1853/62706.

Council of Science Editors:

Haresamudram H. The role of representations in human activity recognition. [Masters Thesis]. Georgia Tech; 2019. Available from: http://hdl.handle.net/1853/62706


Georgia Tech

5. Li, Yinghao. Syntactically guided text generation.

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

 In recent years, as researchers have achieved breakthrough in the generic text generation, increased works turned their attention to controllable text generation to imply external… (more)

Subjects/Keywords: Text generation; Transformer; VAE; Paraphrase

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APA (6th Edition):

Li, Y. (2020). Syntactically guided text generation. (Masters Thesis). Georgia Tech. Retrieved from http://hdl.handle.net/1853/62836

Chicago Manual of Style (16th Edition):

Li, Yinghao. “Syntactically guided text generation.” 2020. Masters Thesis, Georgia Tech. Accessed October 01, 2020. http://hdl.handle.net/1853/62836.

MLA Handbook (7th Edition):

Li, Yinghao. “Syntactically guided text generation.” 2020. Web. 01 Oct 2020.

Vancouver:

Li Y. Syntactically guided text generation. [Internet] [Masters thesis]. Georgia Tech; 2020. [cited 2020 Oct 01]. Available from: http://hdl.handle.net/1853/62836.

Council of Science Editors:

Li Y. Syntactically guided text generation. [Masters Thesis]. Georgia Tech; 2020. Available from: http://hdl.handle.net/1853/62836


Georgia Tech

6. Wishon, Michael Joseph Doumit. Harnessing nonlinear dynamics for applications in high speed information processing.

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

 External-cavity lasers (ECLs) are characterized by nonlinear dynamics created when a laser is subjected to optical feedback from a distant reflector. ECLs were studied using… (more)

Subjects/Keywords: Nonlinear dynamics; Microwave photonics

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APA (6th Edition):

Wishon, M. J. D. (2018). Harnessing nonlinear dynamics for applications in high speed information processing. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/60314

Chicago Manual of Style (16th Edition):

Wishon, Michael Joseph Doumit. “Harnessing nonlinear dynamics for applications in high speed information processing.” 2018. Doctoral Dissertation, Georgia Tech. Accessed October 01, 2020. http://hdl.handle.net/1853/60314.

MLA Handbook (7th Edition):

Wishon, Michael Joseph Doumit. “Harnessing nonlinear dynamics for applications in high speed information processing.” 2018. Web. 01 Oct 2020.

Vancouver:

Wishon MJD. Harnessing nonlinear dynamics for applications in high speed information processing. [Internet] [Doctoral dissertation]. Georgia Tech; 2018. [cited 2020 Oct 01]. Available from: http://hdl.handle.net/1853/60314.

Council of Science Editors:

Wishon MJD. Harnessing nonlinear dynamics for applications in high speed information processing. [Doctoral Dissertation]. Georgia Tech; 2018. Available from: http://hdl.handle.net/1853/60314


Georgia Tech

7. Lim, Juho. Faster than Nyquist signaling based on energy spreading transform and ideal energy spreading transform.

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

 The objective of this thesis is to develop a Faster than Nyquist Signaling (FTNS) scheme which is grounded on EST based Iterative Decision Feedback Equalization… (more)

Subjects/Keywords: Energy spreading transform; Faster than Nyquist signaling; FTN; FTNS; EST

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APA (6th Edition):

Lim, J. (2016). Faster than Nyquist signaling based on energy spreading transform and ideal energy spreading transform. (Masters Thesis). Georgia Tech. Retrieved from http://hdl.handle.net/1853/55533

Chicago Manual of Style (16th Edition):

Lim, Juho. “Faster than Nyquist signaling based on energy spreading transform and ideal energy spreading transform.” 2016. Masters Thesis, Georgia Tech. Accessed October 01, 2020. http://hdl.handle.net/1853/55533.

MLA Handbook (7th Edition):

Lim, Juho. “Faster than Nyquist signaling based on energy spreading transform and ideal energy spreading transform.” 2016. Web. 01 Oct 2020.

Vancouver:

Lim J. Faster than Nyquist signaling based on energy spreading transform and ideal energy spreading transform. [Internet] [Masters thesis]. Georgia Tech; 2016. [cited 2020 Oct 01]. Available from: http://hdl.handle.net/1853/55533.

Council of Science Editors:

Lim J. Faster than Nyquist signaling based on energy spreading transform and ideal energy spreading transform. [Masters Thesis]. Georgia Tech; 2016. Available from: http://hdl.handle.net/1853/55533

8. Gong, Yunyi. Design of switch-less silicon-germanium bi-directional amplifier for loss compensation in passive transmit/receive modules.

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

 The objective of the proposed research is to investigate the design of switch-less bi-directional amplifier (BDA) for loss compensation in passive transmit/receive (T/R) modules, using… (more)

Subjects/Keywords: Bi-directional; Phased array; SiGe BiCMOS

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APA (6th Edition):

Gong, Y. (2018). Design of switch-less silicon-germanium bi-directional amplifier for loss compensation in passive transmit/receive modules. (Masters Thesis). Georgia Tech. Retrieved from http://hdl.handle.net/1853/61129

Chicago Manual of Style (16th Edition):

Gong, Yunyi. “Design of switch-less silicon-germanium bi-directional amplifier for loss compensation in passive transmit/receive modules.” 2018. Masters Thesis, Georgia Tech. Accessed October 01, 2020. http://hdl.handle.net/1853/61129.

MLA Handbook (7th Edition):

Gong, Yunyi. “Design of switch-less silicon-germanium bi-directional amplifier for loss compensation in passive transmit/receive modules.” 2018. Web. 01 Oct 2020.

Vancouver:

Gong Y. Design of switch-less silicon-germanium bi-directional amplifier for loss compensation in passive transmit/receive modules. [Internet] [Masters thesis]. Georgia Tech; 2018. [cited 2020 Oct 01]. Available from: http://hdl.handle.net/1853/61129.

Council of Science Editors:

Gong Y. Design of switch-less silicon-germanium bi-directional amplifier for loss compensation in passive transmit/receive modules. [Masters Thesis]. Georgia Tech; 2018. Available from: http://hdl.handle.net/1853/61129


Georgia Tech

9. Pawar, Rahul Shivaji. Audio diarization for LENA data and its application to computing language behavior statistics for individuals with autism.

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

 The objective of this dissertation is to develop diarization algorithms for LENA data and study its application to compute language behavior statistics for individuals with… (more)

Subjects/Keywords: Diarization; Autism

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APA (6th Edition):

Pawar, R. S. (2019). Audio diarization for LENA data and its application to computing language behavior statistics for individuals with autism. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/62285

Chicago Manual of Style (16th Edition):

Pawar, Rahul Shivaji. “Audio diarization for LENA data and its application to computing language behavior statistics for individuals with autism.” 2019. Doctoral Dissertation, Georgia Tech. Accessed October 01, 2020. http://hdl.handle.net/1853/62285.

MLA Handbook (7th Edition):

Pawar, Rahul Shivaji. “Audio diarization for LENA data and its application to computing language behavior statistics for individuals with autism.” 2019. Web. 01 Oct 2020.

Vancouver:

Pawar RS. Audio diarization for LENA data and its application to computing language behavior statistics for individuals with autism. [Internet] [Doctoral dissertation]. Georgia Tech; 2019. [cited 2020 Oct 01]. Available from: http://hdl.handle.net/1853/62285.

Council of Science Editors:

Pawar RS. Audio diarization for LENA data and its application to computing language behavior statistics for individuals with autism. [Doctoral Dissertation]. Georgia Tech; 2019. Available from: http://hdl.handle.net/1853/62285


Georgia Tech

10. Li, Wei. Improving mispronunciation detection and enriching diagnostic feedback for non-native learners of Mandarin.

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

 Computer assisted pronunciation training (CAPT) system has been designed to help students improve their speaking skills by providing automatic pronunciation scores and diagnostic feedback. Its… (more)

Subjects/Keywords: Computer assisted pronunciation training; Mispronunciation detection; Corrective feedback generation; Automatic speech attribute detection; Memory-based mispronunciation detectors; Diagnostic decision trees; Soft-target training; Deep models for Mandarin phone and tone verification

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APA (6th Edition):

Li, W. (2019). Improving mispronunciation detection and enriching diagnostic feedback for non-native learners of Mandarin. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/62303

Chicago Manual of Style (16th Edition):

Li, Wei. “Improving mispronunciation detection and enriching diagnostic feedback for non-native learners of Mandarin.” 2019. Doctoral Dissertation, Georgia Tech. Accessed October 01, 2020. http://hdl.handle.net/1853/62303.

MLA Handbook (7th Edition):

Li, Wei. “Improving mispronunciation detection and enriching diagnostic feedback for non-native learners of Mandarin.” 2019. Web. 01 Oct 2020.

Vancouver:

Li W. Improving mispronunciation detection and enriching diagnostic feedback for non-native learners of Mandarin. [Internet] [Doctoral dissertation]. Georgia Tech; 2019. [cited 2020 Oct 01]. Available from: http://hdl.handle.net/1853/62303.

Council of Science Editors:

Li W. Improving mispronunciation detection and enriching diagnostic feedback for non-native learners of Mandarin. [Doctoral Dissertation]. Georgia Tech; 2019. Available from: http://hdl.handle.net/1853/62303


Georgia Tech

11. Sebkhi, Nordine. A novel wireless tongue tracking system for speech applications.

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

 The technological innovation of MagTrack is its ability to track the position of a magnetic tracer wirelessly, and with an accuracy of less than 2… (more)

Subjects/Keywords: Algorithm; Articulograph; Biomedical device; Deep learning; Machine learning; Magnetometers; Motion tracking; Neural network; Nonlinear optimization; Permanent magnet localization; Speech; Tongue tracking; Wearable

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APA (6th Edition):

Sebkhi, N. (2019). A novel wireless tongue tracking system for speech applications. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/62309

Chicago Manual of Style (16th Edition):

Sebkhi, Nordine. “A novel wireless tongue tracking system for speech applications.” 2019. Doctoral Dissertation, Georgia Tech. Accessed October 01, 2020. http://hdl.handle.net/1853/62309.

MLA Handbook (7th Edition):

Sebkhi, Nordine. “A novel wireless tongue tracking system for speech applications.” 2019. Web. 01 Oct 2020.

Vancouver:

Sebkhi N. A novel wireless tongue tracking system for speech applications. [Internet] [Doctoral dissertation]. Georgia Tech; 2019. [cited 2020 Oct 01]. Available from: http://hdl.handle.net/1853/62309.

Council of Science Editors:

Sebkhi N. A novel wireless tongue tracking system for speech applications. [Doctoral Dissertation]. Georgia Tech; 2019. Available from: http://hdl.handle.net/1853/62309


Georgia Tech

12. Cheng, Chieh-Feng. Audio classification and event detection based on small-size weakly labeled data.

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

 The objective of this research is to perform audio event detection and classification using small-size weakly labeled data. Although audio event detection has been studied… (more)

Subjects/Keywords: Weakly-labeled data; Audio event detection; Machine learning; Small-size sataset

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APA (6th Edition):

Cheng, C. (2019). Audio classification and event detection based on small-size weakly labeled data. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/62715

Chicago Manual of Style (16th Edition):

Cheng, Chieh-Feng. “Audio classification and event detection based on small-size weakly labeled data.” 2019. Doctoral Dissertation, Georgia Tech. Accessed October 01, 2020. http://hdl.handle.net/1853/62715.

MLA Handbook (7th Edition):

Cheng, Chieh-Feng. “Audio classification and event detection based on small-size weakly labeled data.” 2019. Web. 01 Oct 2020.

Vancouver:

Cheng C. Audio classification and event detection based on small-size weakly labeled data. [Internet] [Doctoral dissertation]. Georgia Tech; 2019. [cited 2020 Oct 01]. Available from: http://hdl.handle.net/1853/62715.

Council of Science Editors:

Cheng C. Audio classification and event detection based on small-size weakly labeled data. [Doctoral Dissertation]. Georgia Tech; 2019. Available from: http://hdl.handle.net/1853/62715


Georgia Tech

13. English, Brittney Ann. A physical therapy system for encouraging specific motion in wrist rehabilitation exercises.

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

 The objective this research is to design a passive therapy device with rehabilitation gaming suite that employs an adaptive algorithm that alters game play in… (more)

Subjects/Keywords: Rehabilitation robotics

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APA (6th Edition):

English, B. A. (2018). A physical therapy system for encouraging specific motion in wrist rehabilitation exercises. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/62181

Chicago Manual of Style (16th Edition):

English, Brittney Ann. “A physical therapy system for encouraging specific motion in wrist rehabilitation exercises.” 2018. Doctoral Dissertation, Georgia Tech. Accessed October 01, 2020. http://hdl.handle.net/1853/62181.

MLA Handbook (7th Edition):

English, Brittney Ann. “A physical therapy system for encouraging specific motion in wrist rehabilitation exercises.” 2018. Web. 01 Oct 2020.

Vancouver:

English BA. A physical therapy system for encouraging specific motion in wrist rehabilitation exercises. [Internet] [Doctoral dissertation]. Georgia Tech; 2018. [cited 2020 Oct 01]. Available from: http://hdl.handle.net/1853/62181.

Council of Science Editors:

English BA. A physical therapy system for encouraging specific motion in wrist rehabilitation exercises. [Doctoral Dissertation]. Georgia Tech; 2018. Available from: http://hdl.handle.net/1853/62181


Georgia Tech

14. Chen, Hua. Single channel speech enhancement with residual learning and recurrent network.

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

 For speech enhancement tasks, non-stationary noise such as babble noise is much harder to suppress than stationary noise. In low SNR environment, it is even… (more)

Subjects/Keywords: Speech enhancement; Machine learning; ResNet; Convolutional recurrent neural network

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APA (6th Edition):

Chen, H. (2020). Single channel speech enhancement with residual learning and recurrent network. (Masters Thesis). Georgia Tech. Retrieved from http://hdl.handle.net/1853/62839

Chicago Manual of Style (16th Edition):

Chen, Hua. “Single channel speech enhancement with residual learning and recurrent network.” 2020. Masters Thesis, Georgia Tech. Accessed October 01, 2020. http://hdl.handle.net/1853/62839.

MLA Handbook (7th Edition):

Chen, Hua. “Single channel speech enhancement with residual learning and recurrent network.” 2020. Web. 01 Oct 2020.

Vancouver:

Chen H. Single channel speech enhancement with residual learning and recurrent network. [Internet] [Masters thesis]. Georgia Tech; 2020. [cited 2020 Oct 01]. Available from: http://hdl.handle.net/1853/62839.

Council of Science Editors:

Chen H. Single channel speech enhancement with residual learning and recurrent network. [Masters Thesis]. Georgia Tech; 2020. Available from: http://hdl.handle.net/1853/62839


Georgia Tech

15. Mejri, Mohamed. Prediction of inner wood defects from outer bark shape.

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

 The analysis of the internal structure of trees is highly important for both forest experts, biological scientists, and the wood industry. Traditionally, CT-scanners are considered… (more)

Subjects/Keywords: Outer shape to inner density prediction; Voxel-wise prediction; Sequence-to-sequence prediction

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APA (6th Edition):

Mejri, M. (2020). Prediction of inner wood defects from outer bark shape. (Masters Thesis). Georgia Tech. Retrieved from http://hdl.handle.net/1853/62864

Chicago Manual of Style (16th Edition):

Mejri, Mohamed. “Prediction of inner wood defects from outer bark shape.” 2020. Masters Thesis, Georgia Tech. Accessed October 01, 2020. http://hdl.handle.net/1853/62864.

MLA Handbook (7th Edition):

Mejri, Mohamed. “Prediction of inner wood defects from outer bark shape.” 2020. Web. 01 Oct 2020.

Vancouver:

Mejri M. Prediction of inner wood defects from outer bark shape. [Internet] [Masters thesis]. Georgia Tech; 2020. [cited 2020 Oct 01]. Available from: http://hdl.handle.net/1853/62864.

Council of Science Editors:

Mejri M. Prediction of inner wood defects from outer bark shape. [Masters Thesis]. Georgia Tech; 2020. Available from: http://hdl.handle.net/1853/62864


Georgia Tech

16. Alfarraj, Motaz A. Learning from seismic data to characterize subsurface volumes.

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

 The exponential growth of collected data from seismic surveys makes it impossible for interpreters to manually inspect, analyze and annotate all collected data. Deep learning… (more)

Subjects/Keywords: Deep learning; Semi-supervised learning; Sequence modeling; Subsurface characterization; Seismic inversion

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APA (6th Edition):

Alfarraj, M. A. (2019). Learning from seismic data to characterize subsurface volumes. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/62310

Chicago Manual of Style (16th Edition):

Alfarraj, Motaz A. “Learning from seismic data to characterize subsurface volumes.” 2019. Doctoral Dissertation, Georgia Tech. Accessed October 01, 2020. http://hdl.handle.net/1853/62310.

MLA Handbook (7th Edition):

Alfarraj, Motaz A. “Learning from seismic data to characterize subsurface volumes.” 2019. Web. 01 Oct 2020.

Vancouver:

Alfarraj MA. Learning from seismic data to characterize subsurface volumes. [Internet] [Doctoral dissertation]. Georgia Tech; 2019. [cited 2020 Oct 01]. Available from: http://hdl.handle.net/1853/62310.

Council of Science Editors:

Alfarraj MA. Learning from seismic data to characterize subsurface volumes. [Doctoral Dissertation]. Georgia Tech; 2019. Available from: http://hdl.handle.net/1853/62310


Georgia Tech

17. Raza, Syed H. Temporally consistent semantic segmentation in videos.

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

 The objective of this Thesis research is to develop algorithms for temporally consistent semantic segmentation in videos. Though many different forms of semantic segmentations exist,… (more)

Subjects/Keywords: Semantic segmentation; Temporal consistency; Causality; Videos; Occlusion boundaries; Depth estimation

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APA (6th Edition):

Raza, S. H. (2014). Temporally consistent semantic segmentation in videos. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/53455

Chicago Manual of Style (16th Edition):

Raza, Syed H. “Temporally consistent semantic segmentation in videos.” 2014. Doctoral Dissertation, Georgia Tech. Accessed October 01, 2020. http://hdl.handle.net/1853/53455.

MLA Handbook (7th Edition):

Raza, Syed H. “Temporally consistent semantic segmentation in videos.” 2014. Web. 01 Oct 2020.

Vancouver:

Raza SH. Temporally consistent semantic segmentation in videos. [Internet] [Doctoral dissertation]. Georgia Tech; 2014. [cited 2020 Oct 01]. Available from: http://hdl.handle.net/1853/53455.

Council of Science Editors:

Raza SH. Temporally consistent semantic segmentation in videos. [Doctoral Dissertation]. Georgia Tech; 2014. Available from: http://hdl.handle.net/1853/53455


Georgia Tech

18. George, Jason. Harnessing resilience: biased voltage overscaling for probabilistic signal processing.

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

 A central component of modern computing is the idea that computation requires determinism. Contrary to this belief, the primary contribution of this work shows that… (more)

Subjects/Keywords: Low power; Error prone; Probabilistic computing; Reduced-precision; Probabilistic CMOS; PCMOS; Biased voltage overscaling; BIVOS; Fixed-point arithmetic; Signal processing; Electric power consumption; Energy conservation

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APA (6th Edition):

George, J. (2011). Harnessing resilience: biased voltage overscaling for probabilistic signal processing. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/42812

Chicago Manual of Style (16th Edition):

George, Jason. “Harnessing resilience: biased voltage overscaling for probabilistic signal processing.” 2011. Doctoral Dissertation, Georgia Tech. Accessed October 01, 2020. http://hdl.handle.net/1853/42812.

MLA Handbook (7th Edition):

George, Jason. “Harnessing resilience: biased voltage overscaling for probabilistic signal processing.” 2011. Web. 01 Oct 2020.

Vancouver:

George J. Harnessing resilience: biased voltage overscaling for probabilistic signal processing. [Internet] [Doctoral dissertation]. Georgia Tech; 2011. [cited 2020 Oct 01]. Available from: http://hdl.handle.net/1853/42812.

Council of Science Editors:

George J. Harnessing resilience: biased voltage overscaling for probabilistic signal processing. [Doctoral Dissertation]. Georgia Tech; 2011. Available from: http://hdl.handle.net/1853/42812


Georgia Tech

19. 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 October 01, 2020. http://hdl.handle.net/1853/45873.

MLA Handbook (7th Edition):

Luo, Chenchi. “Non-uniform sampling: algorithms and architectures.” 2012. Web. 01 Oct 2020.

Vancouver:

Luo C. Non-uniform sampling: algorithms and architectures. [Internet] [Doctoral dissertation]. Georgia Tech; 2012. [cited 2020 Oct 01]. 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

20. Ramakrishnan, Shubha. A system design approach to neuromorphic classifiers.

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

 This work considers alternative strategies to mainstream digital approaches to signal processing - namely analog and neuromorphic solutions, for increased computing efficiency. In the context… (more)

Subjects/Keywords: Analog signal processing; Machine learning; Bio-inspired; Signal processing; Neural networks (Computer science); Analog integrated circuits

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APA (6th Edition):

Ramakrishnan, S. (2013). A system design approach to neuromorphic classifiers. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/51718

Chicago Manual of Style (16th Edition):

Ramakrishnan, Shubha. “A system design approach to neuromorphic classifiers.” 2013. Doctoral Dissertation, Georgia Tech. Accessed October 01, 2020. http://hdl.handle.net/1853/51718.

MLA Handbook (7th Edition):

Ramakrishnan, Shubha. “A system design approach to neuromorphic classifiers.” 2013. Web. 01 Oct 2020.

Vancouver:

Ramakrishnan S. A system design approach to neuromorphic classifiers. [Internet] [Doctoral dissertation]. Georgia Tech; 2013. [cited 2020 Oct 01]. Available from: http://hdl.handle.net/1853/51718.

Council of Science Editors:

Ramakrishnan S. A system design approach to neuromorphic classifiers. [Doctoral Dissertation]. Georgia Tech; 2013. Available from: http://hdl.handle.net/1853/51718


Georgia Tech

21. Shapero, Samuel Andre. Configurable analog hardware for neuromorphic Bayesian inference and least-squares solutions.

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

 Sparse approximation is a Bayesian inference program with a wide number of signal processing applications, such as Compressed Sensing recovery used in medical imaging. Previous… (more)

Subjects/Keywords: Regularized least-squares; Sparse approximation; Analog circuits; FPAA; Neural network; Hopfield network; Locally competitive algorithm (LCA); Least squares; Bayesian statistical decision theory; Analog computers

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APA (6th Edition):

Shapero, S. A. (2013). Configurable analog hardware for neuromorphic Bayesian inference and least-squares solutions. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/51719

Chicago Manual of Style (16th Edition):

Shapero, Samuel Andre. “Configurable analog hardware for neuromorphic Bayesian inference and least-squares solutions.” 2013. Doctoral Dissertation, Georgia Tech. Accessed October 01, 2020. http://hdl.handle.net/1853/51719.

MLA Handbook (7th Edition):

Shapero, Samuel Andre. “Configurable analog hardware for neuromorphic Bayesian inference and least-squares solutions.” 2013. Web. 01 Oct 2020.

Vancouver:

Shapero SA. Configurable analog hardware for neuromorphic Bayesian inference and least-squares solutions. [Internet] [Doctoral dissertation]. Georgia Tech; 2013. [cited 2020 Oct 01]. Available from: http://hdl.handle.net/1853/51719.

Council of Science Editors:

Shapero SA. Configurable analog hardware for neuromorphic Bayesian inference and least-squares solutions. [Doctoral Dissertation]. Georgia Tech; 2013. Available from: http://hdl.handle.net/1853/51719


Georgia Tech

22. Nguyen, Van. Non-contact physiologically related motion sensing with ultra-wideband impulse radar.

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

 Impulse Radio Ultra-wideband (IR-UWB) radar is a promising tool for non-contact, non-invasive sensing of physiological parameters, which could be valuable in identifying or preventing clinical… (more)

Subjects/Keywords: Non-contact; UWB radar; Heart rate estimation; Respiration rate estimation; Chest displacement estimation; Posture change detection; Vital signs monitoring

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APA (6th Edition):

Nguyen, V. (2016). Non-contact physiologically related motion sensing with ultra-wideband impulse radar. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/59142

Chicago Manual of Style (16th Edition):

Nguyen, Van. “Non-contact physiologically related motion sensing with ultra-wideband impulse radar.” 2016. Doctoral Dissertation, Georgia Tech. Accessed October 01, 2020. http://hdl.handle.net/1853/59142.

MLA Handbook (7th Edition):

Nguyen, Van. “Non-contact physiologically related motion sensing with ultra-wideband impulse radar.” 2016. Web. 01 Oct 2020.

Vancouver:

Nguyen V. Non-contact physiologically related motion sensing with ultra-wideband impulse radar. [Internet] [Doctoral dissertation]. Georgia Tech; 2016. [cited 2020 Oct 01]. Available from: http://hdl.handle.net/1853/59142.

Council of Science Editors:

Nguyen V. Non-contact physiologically related motion sensing with ultra-wideband impulse radar. [Doctoral Dissertation]. Georgia Tech; 2016. Available from: http://hdl.handle.net/1853/59142


Georgia Tech

23. Garver, Paul W. MAC layer assisted localization in wireless environments with multiple sensors and multiple emitters.

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

 Extreme emitter density (EED) RF environments, defined as 10k-100k emitters within a footprint of less than 1 km squared, are becoming increasingly common with the… (more)

Subjects/Keywords: MAC layer; Localization; Data association; Time difference of arrival

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APA (6th Edition):

Garver, P. W. (2017). MAC layer assisted localization in wireless environments with multiple sensors and multiple emitters. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/59224

Chicago Manual of Style (16th Edition):

Garver, Paul W. “MAC layer assisted localization in wireless environments with multiple sensors and multiple emitters.” 2017. Doctoral Dissertation, Georgia Tech. Accessed October 01, 2020. http://hdl.handle.net/1853/59224.

MLA Handbook (7th Edition):

Garver, Paul W. “MAC layer assisted localization in wireless environments with multiple sensors and multiple emitters.” 2017. Web. 01 Oct 2020.

Vancouver:

Garver PW. MAC layer assisted localization in wireless environments with multiple sensors and multiple emitters. [Internet] [Doctoral dissertation]. Georgia Tech; 2017. [cited 2020 Oct 01]. Available from: http://hdl.handle.net/1853/59224.

Council of Science Editors:

Garver PW. MAC layer assisted localization in wireless environments with multiple sensors and multiple emitters. [Doctoral Dissertation]. Georgia Tech; 2017. Available from: http://hdl.handle.net/1853/59224


Georgia Tech

24. Ashouri, Hazar. Robust estimation of systolic time intervals using ballistocardiogram and seismocardiogram signals.

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

 The objective of this dissertation is to Pave the way for non-invasive out-of-clinic monitoring of patients with heart failure using systolic time intervals (STIs) obtained… (more)

Subjects/Keywords: Seimocardiogram; Ballistocadiogram; Heart failure; Systolic time intervals

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APA (6th Edition):

Ashouri, H. (2017). Robust estimation of systolic time intervals using ballistocardiogram and seismocardiogram signals. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/59819

Chicago Manual of Style (16th Edition):

Ashouri, Hazar. “Robust estimation of systolic time intervals using ballistocardiogram and seismocardiogram signals.” 2017. Doctoral Dissertation, Georgia Tech. Accessed October 01, 2020. http://hdl.handle.net/1853/59819.

MLA Handbook (7th Edition):

Ashouri, Hazar. “Robust estimation of systolic time intervals using ballistocardiogram and seismocardiogram signals.” 2017. Web. 01 Oct 2020.

Vancouver:

Ashouri H. Robust estimation of systolic time intervals using ballistocardiogram and seismocardiogram signals. [Internet] [Doctoral dissertation]. Georgia Tech; 2017. [cited 2020 Oct 01]. Available from: http://hdl.handle.net/1853/59819.

Council of Science Editors:

Ashouri H. Robust estimation of systolic time intervals using ballistocardiogram and seismocardiogram signals. [Doctoral Dissertation]. Georgia Tech; 2017. Available from: http://hdl.handle.net/1853/59819


Georgia Tech

25. Shafiq, Muhammad Amir. Computational seismic interpretation using attention models, texture dissimilarity, and learning.

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

 The exploration of oil and gas is a vital part of today's increasing power demands to meet the energy we need to power our homes,… (more)

Subjects/Keywords: Seismic interpretation; Automation; Gradient of texture; Visual saliency; Salsi; SeisSal; Unsupervised learning; Autoencoder; 3D FFT; Multispectral projections; Directional center-surround; Feature maps; Human visual system; Texture dissimilarity; F3 block; Netherlands; North Sea; SEAM; Great South Basin; New Zealand; Stratton; Listric faults; Texas Gulf Coast; Sparse classification

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APA (6th Edition):

Shafiq, M. A. (2018). Computational seismic interpretation using attention models, texture dissimilarity, and learning. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/59889

Chicago Manual of Style (16th Edition):

Shafiq, Muhammad Amir. “Computational seismic interpretation using attention models, texture dissimilarity, and learning.” 2018. Doctoral Dissertation, Georgia Tech. Accessed October 01, 2020. http://hdl.handle.net/1853/59889.

MLA Handbook (7th Edition):

Shafiq, Muhammad Amir. “Computational seismic interpretation using attention models, texture dissimilarity, and learning.” 2018. Web. 01 Oct 2020.

Vancouver:

Shafiq MA. Computational seismic interpretation using attention models, texture dissimilarity, and learning. [Internet] [Doctoral dissertation]. Georgia Tech; 2018. [cited 2020 Oct 01]. Available from: http://hdl.handle.net/1853/59889.

Council of Science Editors:

Shafiq MA. Computational seismic interpretation using attention models, texture dissimilarity, and learning. [Doctoral Dissertation]. Georgia Tech; 2018. Available from: http://hdl.handle.net/1853/59889


Georgia Tech

26. 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 October 01, 2020. http://hdl.handle.net/1853/59919.

MLA Handbook (7th Edition):

Whitaker, Bradley M. “Modifying sparse coding to model imbalanced datasets.” 2018. Web. 01 Oct 2020.

Vancouver:

Whitaker BM. Modifying sparse coding to model imbalanced datasets. [Internet] [Doctoral dissertation]. Georgia Tech; 2018. [cited 2020 Oct 01]. 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

27. Hu, Yuting. Texture representation and analysis in material classification and characterization.

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

 Objects and scenes in the real world exhibit abundant textural information. Textures observed in the surfaces of natural objects are not only the appearance of… (more)

Subjects/Keywords: Texture representation; Texture characterization; Deep learning; Texture classification; Texture tracking; Texture analysis; Texture dataset; Material recognition; Material surface characterization

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APA (6th Edition):

Hu, Y. (2019). Texture representation and analysis in material classification and characterization. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/61735

Chicago Manual of Style (16th Edition):

Hu, Yuting. “Texture representation and analysis in material classification and characterization.” 2019. Doctoral Dissertation, Georgia Tech. Accessed October 01, 2020. http://hdl.handle.net/1853/61735.

MLA Handbook (7th Edition):

Hu, Yuting. “Texture representation and analysis in material classification and characterization.” 2019. Web. 01 Oct 2020.

Vancouver:

Hu Y. Texture representation and analysis in material classification and characterization. [Internet] [Doctoral dissertation]. Georgia Tech; 2019. [cited 2020 Oct 01]. Available from: http://hdl.handle.net/1853/61735.

Council of Science Editors:

Hu Y. Texture representation and analysis in material classification and characterization. [Doctoral Dissertation]. Georgia Tech; 2019. Available from: http://hdl.handle.net/1853/61735


Georgia Tech

28. Altaf, Muhammad Umair Bin. Environmental sounds: acquisition, analysis, and representation.

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

 The dissertation presents the design and development of a systematic signal analysis and representation framework beyond short-time Fourier power spectrum for sounds, in particular environmental… (more)

Subjects/Keywords: Environmental sounds; Digital signal processing

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APA (6th Edition):

Altaf, M. U. B. (2015). Environmental sounds: acquisition, analysis, and representation. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/53953

Chicago Manual of Style (16th Edition):

Altaf, Muhammad Umair Bin. “Environmental sounds: acquisition, analysis, and representation.” 2015. Doctoral Dissertation, Georgia Tech. Accessed October 01, 2020. http://hdl.handle.net/1853/53953.

MLA Handbook (7th Edition):

Altaf, Muhammad Umair Bin. “Environmental sounds: acquisition, analysis, and representation.” 2015. Web. 01 Oct 2020.

Vancouver:

Altaf MUB. Environmental sounds: acquisition, analysis, and representation. [Internet] [Doctoral dissertation]. Georgia Tech; 2015. [cited 2020 Oct 01]. Available from: http://hdl.handle.net/1853/53953.

Council of Science Editors:

Altaf MUB. Environmental sounds: acquisition, analysis, and representation. [Doctoral Dissertation]. Georgia Tech; 2015. Available from: http://hdl.handle.net/1853/53953


Georgia Tech

29. Kim, Ha Yang. Modeling and tracking time-varying clock drifts in wireless networks.

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

 Clock synchronization is one of fundamental requirements in distributed networks. However, the imperfection of crystal oscillators is a potential hurdle for network-wide collaboration and degrades… (more)

Subjects/Keywords: Clock synchronization; Clock drift; Measurement

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APA (6th Edition):

Kim, H. Y. (2014). Modeling and tracking time-varying clock drifts in wireless networks. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/53988

Chicago Manual of Style (16th Edition):

Kim, Ha Yang. “Modeling and tracking time-varying clock drifts in wireless networks.” 2014. Doctoral Dissertation, Georgia Tech. Accessed October 01, 2020. http://hdl.handle.net/1853/53988.

MLA Handbook (7th Edition):

Kim, Ha Yang. “Modeling and tracking time-varying clock drifts in wireless networks.” 2014. Web. 01 Oct 2020.

Vancouver:

Kim HY. Modeling and tracking time-varying clock drifts in wireless networks. [Internet] [Doctoral dissertation]. Georgia Tech; 2014. [cited 2020 Oct 01]. Available from: http://hdl.handle.net/1853/53988.

Council of Science Editors:

Kim HY. Modeling and tracking time-varying clock drifts in wireless networks. [Doctoral Dissertation]. Georgia Tech; 2014. Available from: http://hdl.handle.net/1853/53988


Georgia Tech

30. Bhatta, Debesh. Algorithms and methodology for incoherent undersampling based acquisition of high speed signal waveforms using low cost test instrumentation.

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

 The objective of this research is to develop and demonstrate low-complexity, robust, frequency-scalable, wide-band waveform acquisition techniques for testing high speed com- munication systems. High… (more)

Subjects/Keywords: Incoherent undersampling; Low cost testing; Waveform acquisition; High-speed testing

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APA (6th Edition):

Bhatta, D. (2014). Algorithms and methodology for incoherent undersampling based acquisition of high speed signal waveforms using low cost test instrumentation. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/54262

Chicago Manual of Style (16th Edition):

Bhatta, Debesh. “Algorithms and methodology for incoherent undersampling based acquisition of high speed signal waveforms using low cost test instrumentation.” 2014. Doctoral Dissertation, Georgia Tech. Accessed October 01, 2020. http://hdl.handle.net/1853/54262.

MLA Handbook (7th Edition):

Bhatta, Debesh. “Algorithms and methodology for incoherent undersampling based acquisition of high speed signal waveforms using low cost test instrumentation.” 2014. Web. 01 Oct 2020.

Vancouver:

Bhatta D. Algorithms and methodology for incoherent undersampling based acquisition of high speed signal waveforms using low cost test instrumentation. [Internet] [Doctoral dissertation]. Georgia Tech; 2014. [cited 2020 Oct 01]. Available from: http://hdl.handle.net/1853/54262.

Council of Science Editors:

Bhatta D. Algorithms and methodology for incoherent undersampling based acquisition of high speed signal waveforms using low cost test instrumentation. [Doctoral Dissertation]. Georgia Tech; 2014. Available from: http://hdl.handle.net/1853/54262

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