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You searched for +publisher:"Virginia Tech" +contributor:("Abbott, Amos L."). Showing records 1 – 30 of 100 total matches.

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Virginia Tech

1. Xiao, Yao. Vehicle Detection in Deep Learning.

Degree: MS, Computer Engineering, 2019, Virginia Tech

 Computer vision techniques are becoming increasingly popular. For example, face recognition is used to help police find criminals, vehicle detection is used to prevent drivers… (more)

Subjects/Keywords: Vehicle Detection; Deep Learning; Convolutional Neural Networks; Image Processing; Architecture Design

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APA (6th Edition):

Xiao, Y. (2019). Vehicle Detection in Deep Learning. (Masters Thesis). Virginia Tech. Retrieved from http://hdl.handle.net/10919/91375

Chicago Manual of Style (16th Edition):

Xiao, Yao. “Vehicle Detection in Deep Learning.” 2019. Masters Thesis, Virginia Tech. Accessed October 21, 2020. http://hdl.handle.net/10919/91375.

MLA Handbook (7th Edition):

Xiao, Yao. “Vehicle Detection in Deep Learning.” 2019. Web. 21 Oct 2020.

Vancouver:

Xiao Y. Vehicle Detection in Deep Learning. [Internet] [Masters thesis]. Virginia Tech; 2019. [cited 2020 Oct 21]. Available from: http://hdl.handle.net/10919/91375.

Council of Science Editors:

Xiao Y. Vehicle Detection in Deep Learning. [Masters Thesis]. Virginia Tech; 2019. Available from: http://hdl.handle.net/10919/91375


Virginia Tech

2. Bianchi, Eric Loran. COCO-Bridge: Common Objects in Context Dataset and Benchmark for Structural Detail Detection of Bridges.

Degree: MS, Civil Engineering, 2019, Virginia Tech

 Common Objects in Context for bridge inspection (COCO-Bridge) was introduced to improve a drone-conducted bridge inspection process. Drones are a great tool for bridge inspectors… (more)

Subjects/Keywords: Convolutional neural network; bridge inspection; UAS; CNN; Artificial Intelligence; Augmented Reality; Deep Learning; Machine Learning

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APA (6th Edition):

Bianchi, E. L. (2019). COCO-Bridge: Common Objects in Context Dataset and Benchmark for Structural Detail Detection of Bridges. (Masters Thesis). Virginia Tech. Retrieved from http://hdl.handle.net/10919/87588

Chicago Manual of Style (16th Edition):

Bianchi, Eric Loran. “COCO-Bridge: Common Objects in Context Dataset and Benchmark for Structural Detail Detection of Bridges.” 2019. Masters Thesis, Virginia Tech. Accessed October 21, 2020. http://hdl.handle.net/10919/87588.

MLA Handbook (7th Edition):

Bianchi, Eric Loran. “COCO-Bridge: Common Objects in Context Dataset and Benchmark for Structural Detail Detection of Bridges.” 2019. Web. 21 Oct 2020.

Vancouver:

Bianchi EL. COCO-Bridge: Common Objects in Context Dataset and Benchmark for Structural Detail Detection of Bridges. [Internet] [Masters thesis]. Virginia Tech; 2019. [cited 2020 Oct 21]. Available from: http://hdl.handle.net/10919/87588.

Council of Science Editors:

Bianchi EL. COCO-Bridge: Common Objects in Context Dataset and Benchmark for Structural Detail Detection of Bridges. [Masters Thesis]. Virginia Tech; 2019. Available from: http://hdl.handle.net/10919/87588


Virginia Tech

3. Hardman, Owen Russell. Optimizing a Network Layer Moving Target Defense by Translating Software from Python to C.

Degree: MS, Computer Engineering, 2016, Virginia Tech

 The security of powerful systems and large networks is often addressed through complex defenses. While these types of defenses offer increased security, they are resource… (more)

Subjects/Keywords: IPv6; Moving Target Defense; Optimizing; Python; C

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APA (6th Edition):

Hardman, O. R. (2016). Optimizing a Network Layer Moving Target Defense by Translating Software from Python to C. (Masters Thesis). Virginia Tech. Retrieved from http://hdl.handle.net/10919/64435

Chicago Manual of Style (16th Edition):

Hardman, Owen Russell. “Optimizing a Network Layer Moving Target Defense by Translating Software from Python to C.” 2016. Masters Thesis, Virginia Tech. Accessed October 21, 2020. http://hdl.handle.net/10919/64435.

MLA Handbook (7th Edition):

Hardman, Owen Russell. “Optimizing a Network Layer Moving Target Defense by Translating Software from Python to C.” 2016. Web. 21 Oct 2020.

Vancouver:

Hardman OR. Optimizing a Network Layer Moving Target Defense by Translating Software from Python to C. [Internet] [Masters thesis]. Virginia Tech; 2016. [cited 2020 Oct 21]. Available from: http://hdl.handle.net/10919/64435.

Council of Science Editors:

Hardman OR. Optimizing a Network Layer Moving Target Defense by Translating Software from Python to C. [Masters Thesis]. Virginia Tech; 2016. Available from: http://hdl.handle.net/10919/64435


Virginia Tech

4. Murali, Dilip Venkateswaran. Verification of Cyber Physical Systems.

Degree: MS, Computer Engineering, 2013, Virginia Tech

 Due to the increasing complexity of today\'s cyber-physical systems, defects become inevitable and harder to detect. The complexity of such software is generally huge, with… (more)

Subjects/Keywords: Invariants detection; Symbolic Execution; KLEE; Cloud9; VCC

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APA (6th Edition):

Murali, D. V. (2013). Verification of Cyber Physical Systems. (Masters Thesis). Virginia Tech. Retrieved from http://hdl.handle.net/10919/23824

Chicago Manual of Style (16th Edition):

Murali, Dilip Venkateswaran. “Verification of Cyber Physical Systems.” 2013. Masters Thesis, Virginia Tech. Accessed October 21, 2020. http://hdl.handle.net/10919/23824.

MLA Handbook (7th Edition):

Murali, Dilip Venkateswaran. “Verification of Cyber Physical Systems.” 2013. Web. 21 Oct 2020.

Vancouver:

Murali DV. Verification of Cyber Physical Systems. [Internet] [Masters thesis]. Virginia Tech; 2013. [cited 2020 Oct 21]. Available from: http://hdl.handle.net/10919/23824.

Council of Science Editors:

Murali DV. Verification of Cyber Physical Systems. [Masters Thesis]. Virginia Tech; 2013. Available from: http://hdl.handle.net/10919/23824


Virginia Tech

5. Kahu, Sampanna Yashwant. Figure Extraction from Scanned Electronic Theses and Dissertations.

Degree: MS, Computer Engineering, 2020, Virginia Tech

 Portable Document Format (PDF) is one of the most popular document formats. However, parsing PDF files is not a trivial task. One use-case of parsing… (more)

Subjects/Keywords: Figure Extraction; Deep Learning; Computer Vision; Digital Libraries

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APA (6th Edition):

Kahu, S. Y. (2020). Figure Extraction from Scanned Electronic Theses and Dissertations. (Masters Thesis). Virginia Tech. Retrieved from http://hdl.handle.net/10919/100113

Chicago Manual of Style (16th Edition):

Kahu, Sampanna Yashwant. “Figure Extraction from Scanned Electronic Theses and Dissertations.” 2020. Masters Thesis, Virginia Tech. Accessed October 21, 2020. http://hdl.handle.net/10919/100113.

MLA Handbook (7th Edition):

Kahu, Sampanna Yashwant. “Figure Extraction from Scanned Electronic Theses and Dissertations.” 2020. Web. 21 Oct 2020.

Vancouver:

Kahu SY. Figure Extraction from Scanned Electronic Theses and Dissertations. [Internet] [Masters thesis]. Virginia Tech; 2020. [cited 2020 Oct 21]. Available from: http://hdl.handle.net/10919/100113.

Council of Science Editors:

Kahu SY. Figure Extraction from Scanned Electronic Theses and Dissertations. [Masters Thesis]. Virginia Tech; 2020. Available from: http://hdl.handle.net/10919/100113


Virginia Tech

6. Freeman, William John. Digital Video Stabilization with Inertial Fusion.

Degree: MS, Electrical Engineering, 2013, Virginia Tech

 As computing power becomes more and more available, robotic systems are moving away from active sensors for environmental awareness and transitioning into passive vision sensors.… (more)

Subjects/Keywords: Image Stabilization; Kalman Filter; Inertial Fusion

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APA (6th Edition):

Freeman, W. J. (2013). Digital Video Stabilization with Inertial Fusion. (Masters Thesis). Virginia Tech. Retrieved from http://hdl.handle.net/10919/23080

Chicago Manual of Style (16th Edition):

Freeman, William John. “Digital Video Stabilization with Inertial Fusion.” 2013. Masters Thesis, Virginia Tech. Accessed October 21, 2020. http://hdl.handle.net/10919/23080.

MLA Handbook (7th Edition):

Freeman, William John. “Digital Video Stabilization with Inertial Fusion.” 2013. Web. 21 Oct 2020.

Vancouver:

Freeman WJ. Digital Video Stabilization with Inertial Fusion. [Internet] [Masters thesis]. Virginia Tech; 2013. [cited 2020 Oct 21]. Available from: http://hdl.handle.net/10919/23080.

Council of Science Editors:

Freeman WJ. Digital Video Stabilization with Inertial Fusion. [Masters Thesis]. Virginia Tech; 2013. Available from: http://hdl.handle.net/10919/23080


Virginia Tech

7. Gaopande, Meghana Laxmidhar. Exploring Accumulated Gradient-Based Quantization and Compression for Deep Neural Networks.

Degree: MS, Computer Engineering, 2020, Virginia Tech

 Neural networks are being employed in many different real-world applications. By learning the complex relationship between the input data and ground-truth output data during the… (more)

Subjects/Keywords: Deep Neural Networks; Quantization; Pruning; Fixed-Point

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APA (6th Edition):

Gaopande, M. L. (2020). Exploring Accumulated Gradient-Based Quantization and Compression for Deep Neural Networks. (Masters Thesis). Virginia Tech. Retrieved from http://hdl.handle.net/10919/98617

Chicago Manual of Style (16th Edition):

Gaopande, Meghana Laxmidhar. “Exploring Accumulated Gradient-Based Quantization and Compression for Deep Neural Networks.” 2020. Masters Thesis, Virginia Tech. Accessed October 21, 2020. http://hdl.handle.net/10919/98617.

MLA Handbook (7th Edition):

Gaopande, Meghana Laxmidhar. “Exploring Accumulated Gradient-Based Quantization and Compression for Deep Neural Networks.” 2020. Web. 21 Oct 2020.

Vancouver:

Gaopande ML. Exploring Accumulated Gradient-Based Quantization and Compression for Deep Neural Networks. [Internet] [Masters thesis]. Virginia Tech; 2020. [cited 2020 Oct 21]. Available from: http://hdl.handle.net/10919/98617.

Council of Science Editors:

Gaopande ML. Exploring Accumulated Gradient-Based Quantization and Compression for Deep Neural Networks. [Masters Thesis]. Virginia Tech; 2020. Available from: http://hdl.handle.net/10919/98617


Virginia Tech

8. Cristy, John Oliver. VText: A Plug-in Extension to Add Electronic Textbook Functionality to Microsoft OneNote.

Degree: MS, Computer Engineering, 2014, Virginia Tech

 Electronic textbooks are different from ebooks (electronic books) in that they allow the user to go beyond just reading material on a computer screen. Electronic… (more)

Subjects/Keywords: Tablet; Electronic Textbook; Active Learning; Microsoft OneNote

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APA (6th Edition):

Cristy, J. O. (2014). VText: A Plug-in Extension to Add Electronic Textbook Functionality to Microsoft OneNote. (Masters Thesis). Virginia Tech. Retrieved from http://hdl.handle.net/10919/25154

Chicago Manual of Style (16th Edition):

Cristy, John Oliver. “VText: A Plug-in Extension to Add Electronic Textbook Functionality to Microsoft OneNote.” 2014. Masters Thesis, Virginia Tech. Accessed October 21, 2020. http://hdl.handle.net/10919/25154.

MLA Handbook (7th Edition):

Cristy, John Oliver. “VText: A Plug-in Extension to Add Electronic Textbook Functionality to Microsoft OneNote.” 2014. Web. 21 Oct 2020.

Vancouver:

Cristy JO. VText: A Plug-in Extension to Add Electronic Textbook Functionality to Microsoft OneNote. [Internet] [Masters thesis]. Virginia Tech; 2014. [cited 2020 Oct 21]. Available from: http://hdl.handle.net/10919/25154.

Council of Science Editors:

Cristy JO. VText: A Plug-in Extension to Add Electronic Textbook Functionality to Microsoft OneNote. [Masters Thesis]. Virginia Tech; 2014. Available from: http://hdl.handle.net/10919/25154


Virginia Tech

9. Bharambe, Sachin Vasant. Smart Environment Based On Real-Time Human Position Tracking For Remote Presence And Collaboration.

Degree: MS, Computer Engineering, 2017, Virginia Tech

 Real-time, virtual and mixed reality systems have diverse uses for real-world data visualization, representation, and remote collaboration in distant learning settings, especially in universities. Design… (more)

Subjects/Keywords: Human position detection; position tracking; network communication; virtual reality; remote presence and collaboration

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APA (6th Edition):

Bharambe, S. V. (2017). Smart Environment Based On Real-Time Human Position Tracking For Remote Presence And Collaboration. (Masters Thesis). Virginia Tech. Retrieved from http://hdl.handle.net/10919/86661

Chicago Manual of Style (16th Edition):

Bharambe, Sachin Vasant. “Smart Environment Based On Real-Time Human Position Tracking For Remote Presence And Collaboration.” 2017. Masters Thesis, Virginia Tech. Accessed October 21, 2020. http://hdl.handle.net/10919/86661.

MLA Handbook (7th Edition):

Bharambe, Sachin Vasant. “Smart Environment Based On Real-Time Human Position Tracking For Remote Presence And Collaboration.” 2017. Web. 21 Oct 2020.

Vancouver:

Bharambe SV. Smart Environment Based On Real-Time Human Position Tracking For Remote Presence And Collaboration. [Internet] [Masters thesis]. Virginia Tech; 2017. [cited 2020 Oct 21]. Available from: http://hdl.handle.net/10919/86661.

Council of Science Editors:

Bharambe SV. Smart Environment Based On Real-Time Human Position Tracking For Remote Presence And Collaboration. [Masters Thesis]. Virginia Tech; 2017. Available from: http://hdl.handle.net/10919/86661


Virginia Tech

10. Messou, Ehounoud Joseph Christopher. Handling Invalid Pixels in Convolutional Neural Networks.

Degree: MS, Computer Engineering, 2020, Virginia Tech

 A module at the heart of deep neural networks built for Artificial Intelligence is the convolutional layer. When multiple convolutional layers are used together with… (more)

Subjects/Keywords: Computer Vision; Padding; Convolution; Invalid pixels

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APA (6th Edition):

Messou, E. J. C. (2020). Handling Invalid Pixels in Convolutional Neural Networks. (Masters Thesis). Virginia Tech. Retrieved from http://hdl.handle.net/10919/98619

Chicago Manual of Style (16th Edition):

Messou, Ehounoud Joseph Christopher. “Handling Invalid Pixels in Convolutional Neural Networks.” 2020. Masters Thesis, Virginia Tech. Accessed October 21, 2020. http://hdl.handle.net/10919/98619.

MLA Handbook (7th Edition):

Messou, Ehounoud Joseph Christopher. “Handling Invalid Pixels in Convolutional Neural Networks.” 2020. Web. 21 Oct 2020.

Vancouver:

Messou EJC. Handling Invalid Pixels in Convolutional Neural Networks. [Internet] [Masters thesis]. Virginia Tech; 2020. [cited 2020 Oct 21]. Available from: http://hdl.handle.net/10919/98619.

Council of Science Editors:

Messou EJC. Handling Invalid Pixels in Convolutional Neural Networks. [Masters Thesis]. Virginia Tech; 2020. Available from: http://hdl.handle.net/10919/98619

11. Nogales, Chris Lorena. Robot Autonomous Fire Location using a Weighted Probability Algorithm.

Degree: MS, Computer Engineering, 2016, Virginia Tech

 Finding a fire inside of a structure without knowing its conditions poses a dangerous threat to the safety of firefighters. As a result, robots are… (more)

Subjects/Keywords: autonomy; perception; machine learning; firefighting robot

Page 1

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APA (6th Edition):

Nogales, C. L. (2016). Robot Autonomous Fire Location using a Weighted Probability Algorithm. (Masters Thesis). Virginia Tech. Retrieved from http://hdl.handle.net/10919/73360

Chicago Manual of Style (16th Edition):

Nogales, Chris Lorena. “Robot Autonomous Fire Location using a Weighted Probability Algorithm.” 2016. Masters Thesis, Virginia Tech. Accessed October 21, 2020. http://hdl.handle.net/10919/73360.

MLA Handbook (7th Edition):

Nogales, Chris Lorena. “Robot Autonomous Fire Location using a Weighted Probability Algorithm.” 2016. Web. 21 Oct 2020.

Vancouver:

Nogales CL. Robot Autonomous Fire Location using a Weighted Probability Algorithm. [Internet] [Masters thesis]. Virginia Tech; 2016. [cited 2020 Oct 21]. Available from: http://hdl.handle.net/10919/73360.

Council of Science Editors:

Nogales CL. Robot Autonomous Fire Location using a Weighted Probability Algorithm. [Masters Thesis]. Virginia Tech; 2016. Available from: http://hdl.handle.net/10919/73360


Virginia Tech

12. Pandit, Shuchi. Novel Architectures for Trace Buffer Design to facilitate Post-Silicon Validation and Test.

Degree: MS, Computer Engineering, 2014, Virginia Tech

 Post-Silicon validation is playing an increasingly important role as more chips are failing in the functional mode due to either manufacturing defects escaped during scan-based… (more)

Subjects/Keywords: Trace Buffer Architecture; Signal Restoration; Invariants

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APA (6th Edition):

Pandit, S. (2014). Novel Architectures for Trace Buffer Design to facilitate Post-Silicon Validation and Test. (Masters Thesis). Virginia Tech. Retrieved from http://hdl.handle.net/10919/49151

Chicago Manual of Style (16th Edition):

Pandit, Shuchi. “Novel Architectures for Trace Buffer Design to facilitate Post-Silicon Validation and Test.” 2014. Masters Thesis, Virginia Tech. Accessed October 21, 2020. http://hdl.handle.net/10919/49151.

MLA Handbook (7th Edition):

Pandit, Shuchi. “Novel Architectures for Trace Buffer Design to facilitate Post-Silicon Validation and Test.” 2014. Web. 21 Oct 2020.

Vancouver:

Pandit S. Novel Architectures for Trace Buffer Design to facilitate Post-Silicon Validation and Test. [Internet] [Masters thesis]. Virginia Tech; 2014. [cited 2020 Oct 21]. Available from: http://hdl.handle.net/10919/49151.

Council of Science Editors:

Pandit S. Novel Architectures for Trace Buffer Design to facilitate Post-Silicon Validation and Test. [Masters Thesis]. Virginia Tech; 2014. Available from: http://hdl.handle.net/10919/49151


Virginia Tech

13. Ye, Yuxian. Study of Sensing Issues in Dynamic Spectrum Access.

Degree: MS, Computer Engineering, 2019, Virginia Tech

 Spectrum relates to the radio frequencies allocated to the federal users and commercial users for communication over the airwaves. It is a sovereign asset that… (more)

Subjects/Keywords: Dynamic Spectrum Access; Spectrum monitoring; Energy harvesting; Energy management; Spectrum users' location privacy preserving

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APA (6th Edition):

Ye, Y. (2019). Study of Sensing Issues in Dynamic Spectrum Access. (Masters Thesis). Virginia Tech. Retrieved from http://hdl.handle.net/10919/90184

Chicago Manual of Style (16th Edition):

Ye, Yuxian. “Study of Sensing Issues in Dynamic Spectrum Access.” 2019. Masters Thesis, Virginia Tech. Accessed October 21, 2020. http://hdl.handle.net/10919/90184.

MLA Handbook (7th Edition):

Ye, Yuxian. “Study of Sensing Issues in Dynamic Spectrum Access.” 2019. Web. 21 Oct 2020.

Vancouver:

Ye Y. Study of Sensing Issues in Dynamic Spectrum Access. [Internet] [Masters thesis]. Virginia Tech; 2019. [cited 2020 Oct 21]. Available from: http://hdl.handle.net/10919/90184.

Council of Science Editors:

Ye Y. Study of Sensing Issues in Dynamic Spectrum Access. [Masters Thesis]. Virginia Tech; 2019. Available from: http://hdl.handle.net/10919/90184


Virginia Tech

14. Gujar, Surabhi Satyajit. Detecting Electromagnetic Injection Attack on FPGAs Using In Situ Timing Sensors.

Degree: MS, Computer Engineering, 2018, Virginia Tech

 Nowadays, security is one of the foremost concerns as the confidence in a system is mostly dependent on its ability to protect itself against any… (more)

Subjects/Keywords: Hardware Security; FPGA; Electromagnetic Injection; Fault Attacks

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APA (6th Edition):

Gujar, S. S. (2018). Detecting Electromagnetic Injection Attack on FPGAs Using In Situ Timing Sensors. (Masters Thesis). Virginia Tech. Retrieved from http://hdl.handle.net/10919/97006

Chicago Manual of Style (16th Edition):

Gujar, Surabhi Satyajit. “Detecting Electromagnetic Injection Attack on FPGAs Using In Situ Timing Sensors.” 2018. Masters Thesis, Virginia Tech. Accessed October 21, 2020. http://hdl.handle.net/10919/97006.

MLA Handbook (7th Edition):

Gujar, Surabhi Satyajit. “Detecting Electromagnetic Injection Attack on FPGAs Using In Situ Timing Sensors.” 2018. Web. 21 Oct 2020.

Vancouver:

Gujar SS. Detecting Electromagnetic Injection Attack on FPGAs Using In Situ Timing Sensors. [Internet] [Masters thesis]. Virginia Tech; 2018. [cited 2020 Oct 21]. Available from: http://hdl.handle.net/10919/97006.

Council of Science Editors:

Gujar SS. Detecting Electromagnetic Injection Attack on FPGAs Using In Situ Timing Sensors. [Masters Thesis]. Virginia Tech; 2018. Available from: http://hdl.handle.net/10919/97006


Virginia Tech

15. Yellapantula, Sudha Ravali. Synthesizing Realistic Data for Vision Based Drone-to-Drone Detection.

Degree: MS, Computer Engineering, 2019, Virginia Tech

 In the recent years, technologies like Deep Learning and Machine Learning have seen many rapid developments. Among the many applications they have, object detection is… (more)

Subjects/Keywords: GANs; Deep Learning; Object Detection

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APA (6th Edition):

Yellapantula, S. R. (2019). Synthesizing Realistic Data for Vision Based Drone-to-Drone Detection. (Masters Thesis). Virginia Tech. Retrieved from http://hdl.handle.net/10919/91460

Chicago Manual of Style (16th Edition):

Yellapantula, Sudha Ravali. “Synthesizing Realistic Data for Vision Based Drone-to-Drone Detection.” 2019. Masters Thesis, Virginia Tech. Accessed October 21, 2020. http://hdl.handle.net/10919/91460.

MLA Handbook (7th Edition):

Yellapantula, Sudha Ravali. “Synthesizing Realistic Data for Vision Based Drone-to-Drone Detection.” 2019. Web. 21 Oct 2020.

Vancouver:

Yellapantula SR. Synthesizing Realistic Data for Vision Based Drone-to-Drone Detection. [Internet] [Masters thesis]. Virginia Tech; 2019. [cited 2020 Oct 21]. Available from: http://hdl.handle.net/10919/91460.

Council of Science Editors:

Yellapantula SR. Synthesizing Realistic Data for Vision Based Drone-to-Drone Detection. [Masters Thesis]. Virginia Tech; 2019. Available from: http://hdl.handle.net/10919/91460


Virginia Tech

16. Bala, Divya Chandrakant. Cell Phenotype Analyzer: Automated Techniques for Cell Phenotyping using Contactless Dielectrophoresis.

Degree: MS, Computer Engineering, 2016, Virginia Tech

 Cancer is among the leading causes of death worldwide. In 2012, there were 14 million new cases and 8.2 million cancer-related deaths worldwide. The number… (more)

Subjects/Keywords: Cell Phenotype; Computer Vision; Dielectrophoresis

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APA (6th Edition):

Bala, D. C. (2016). Cell Phenotype Analyzer: Automated Techniques for Cell Phenotyping using Contactless Dielectrophoresis. (Masters Thesis). Virginia Tech. Retrieved from http://hdl.handle.net/10919/71428

Chicago Manual of Style (16th Edition):

Bala, Divya Chandrakant. “Cell Phenotype Analyzer: Automated Techniques for Cell Phenotyping using Contactless Dielectrophoresis.” 2016. Masters Thesis, Virginia Tech. Accessed October 21, 2020. http://hdl.handle.net/10919/71428.

MLA Handbook (7th Edition):

Bala, Divya Chandrakant. “Cell Phenotype Analyzer: Automated Techniques for Cell Phenotyping using Contactless Dielectrophoresis.” 2016. Web. 21 Oct 2020.

Vancouver:

Bala DC. Cell Phenotype Analyzer: Automated Techniques for Cell Phenotyping using Contactless Dielectrophoresis. [Internet] [Masters thesis]. Virginia Tech; 2016. [cited 2020 Oct 21]. Available from: http://hdl.handle.net/10919/71428.

Council of Science Editors:

Bala DC. Cell Phenotype Analyzer: Automated Techniques for Cell Phenotyping using Contactless Dielectrophoresis. [Masters Thesis]. Virginia Tech; 2016. Available from: http://hdl.handle.net/10919/71428


Virginia Tech

17. Manjunatha Bharadwaj, Sandhya. Land Cover Quantification using Autoencoder based Unsupervised Deep Learning.

Degree: MS, Computer Engineering, 2020, Virginia Tech

 This work aims to develop an automated deep learning model for identifying and estimating the composition of the different land covers in a region using… (more)

Subjects/Keywords: Deep Learning; Autoencoder; Land Cover; Hyperspectral Imagery; Spectral Unmixing; Reflectance Spectra

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APA (6th Edition):

Manjunatha Bharadwaj, S. (2020). Land Cover Quantification using Autoencoder based Unsupervised Deep Learning. (Masters Thesis). Virginia Tech. Retrieved from http://hdl.handle.net/10919/99861

Chicago Manual of Style (16th Edition):

Manjunatha Bharadwaj, Sandhya. “Land Cover Quantification using Autoencoder based Unsupervised Deep Learning.” 2020. Masters Thesis, Virginia Tech. Accessed October 21, 2020. http://hdl.handle.net/10919/99861.

MLA Handbook (7th Edition):

Manjunatha Bharadwaj, Sandhya. “Land Cover Quantification using Autoencoder based Unsupervised Deep Learning.” 2020. Web. 21 Oct 2020.

Vancouver:

Manjunatha Bharadwaj S. Land Cover Quantification using Autoencoder based Unsupervised Deep Learning. [Internet] [Masters thesis]. Virginia Tech; 2020. [cited 2020 Oct 21]. Available from: http://hdl.handle.net/10919/99861.

Council of Science Editors:

Manjunatha Bharadwaj S. Land Cover Quantification using Autoencoder based Unsupervised Deep Learning. [Masters Thesis]. Virginia Tech; 2020. Available from: http://hdl.handle.net/10919/99861


Virginia Tech

18. Munagani, Indira Priya Darshini. Mining Rare Features in Fingerprints using Core points and Triplet-based Features.

Degree: MS, Computer Engineering, 2014, Virginia Tech

 A fingerprint matching algorithm with a novel set of matching parameters based on core points and triangular descriptors is proposed to discover rarity in fingerprints.… (more)

Subjects/Keywords: Fingerprints; Rare Features; Rarity; Latent; Core Points; Triplets; GPU

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APA (6th Edition):

Munagani, I. P. D. (2014). Mining Rare Features in Fingerprints using Core points and Triplet-based Features. (Masters Thesis). Virginia Tech. Retrieved from http://hdl.handle.net/10919/24784

Chicago Manual of Style (16th Edition):

Munagani, Indira Priya Darshini. “Mining Rare Features in Fingerprints using Core points and Triplet-based Features.” 2014. Masters Thesis, Virginia Tech. Accessed October 21, 2020. http://hdl.handle.net/10919/24784.

MLA Handbook (7th Edition):

Munagani, Indira Priya Darshini. “Mining Rare Features in Fingerprints using Core points and Triplet-based Features.” 2014. Web. 21 Oct 2020.

Vancouver:

Munagani IPD. Mining Rare Features in Fingerprints using Core points and Triplet-based Features. [Internet] [Masters thesis]. Virginia Tech; 2014. [cited 2020 Oct 21]. Available from: http://hdl.handle.net/10919/24784.

Council of Science Editors:

Munagani IPD. Mining Rare Features in Fingerprints using Core points and Triplet-based Features. [Masters Thesis]. Virginia Tech; 2014. Available from: http://hdl.handle.net/10919/24784


Virginia Tech

19. Xu, Hao. Safety of Self-driving Cars: A Case Study on Lane Keeping Systems.

Degree: MS, Computer Engineering, 2020, Virginia Tech

 Self-driving cars is a hot topic nowadays. Machine learning is a popular method to achieve self-driving cars. Machine learning constructs a neural network, which imitates… (more)

Subjects/Keywords: Self-driving; Neural Network; Lane Detection; Specification; Enforcement; Delay; Prediction.

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APA (6th Edition):

Xu, H. (2020). Safety of Self-driving Cars: A Case Study on Lane Keeping Systems. (Masters Thesis). Virginia Tech. Retrieved from http://hdl.handle.net/10919/99292

Chicago Manual of Style (16th Edition):

Xu, Hao. “Safety of Self-driving Cars: A Case Study on Lane Keeping Systems.” 2020. Masters Thesis, Virginia Tech. Accessed October 21, 2020. http://hdl.handle.net/10919/99292.

MLA Handbook (7th Edition):

Xu, Hao. “Safety of Self-driving Cars: A Case Study on Lane Keeping Systems.” 2020. Web. 21 Oct 2020.

Vancouver:

Xu H. Safety of Self-driving Cars: A Case Study on Lane Keeping Systems. [Internet] [Masters thesis]. Virginia Tech; 2020. [cited 2020 Oct 21]. Available from: http://hdl.handle.net/10919/99292.

Council of Science Editors:

Xu H. Safety of Self-driving Cars: A Case Study on Lane Keeping Systems. [Masters Thesis]. Virginia Tech; 2020. Available from: http://hdl.handle.net/10919/99292


Virginia Tech

20. Mohapatra, Akrit. Natural Language Driven Image Edits using a Semantic Image Manipulation Language.

Degree: MS, Computer Engineering, 2018, Virginia Tech

 Language provides us with a powerful tool to articulate and express ourselves! Understanding and harnessing the expressions of natural language can open the doors to… (more)

Subjects/Keywords: Machine Learning; Natural language Processing; Computer Vision

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APA (6th Edition):

Mohapatra, A. (2018). Natural Language Driven Image Edits using a Semantic Image Manipulation Language. (Masters Thesis). Virginia Tech. Retrieved from http://hdl.handle.net/10919/83452

Chicago Manual of Style (16th Edition):

Mohapatra, Akrit. “Natural Language Driven Image Edits using a Semantic Image Manipulation Language.” 2018. Masters Thesis, Virginia Tech. Accessed October 21, 2020. http://hdl.handle.net/10919/83452.

MLA Handbook (7th Edition):

Mohapatra, Akrit. “Natural Language Driven Image Edits using a Semantic Image Manipulation Language.” 2018. Web. 21 Oct 2020.

Vancouver:

Mohapatra A. Natural Language Driven Image Edits using a Semantic Image Manipulation Language. [Internet] [Masters thesis]. Virginia Tech; 2018. [cited 2020 Oct 21]. Available from: http://hdl.handle.net/10919/83452.

Council of Science Editors:

Mohapatra A. Natural Language Driven Image Edits using a Semantic Image Manipulation Language. [Masters Thesis]. Virginia Tech; 2018. Available from: http://hdl.handle.net/10919/83452


Virginia Tech

21. Arefiyan Khalilabad, Seyyed Mostafa. Deep Learning Models for Context-Aware Object Detection.

Degree: MS, Computer Engineering, 2017, Virginia Tech

 In this thesis, we present ContextNet, a novel general object detection framework for incorporating context cues into a detection pipeline. Current deep learning methods for… (more)

Subjects/Keywords: Context-aware Detection; Object Detection; Context Modeling; Context Extraction; Convolutional Neural Network; Computer Vision; Deep Learning; Machine Learning

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APA (6th Edition):

Arefiyan Khalilabad, S. M. (2017). Deep Learning Models for Context-Aware Object Detection. (Masters Thesis). Virginia Tech. Retrieved from http://hdl.handle.net/10919/88387

Chicago Manual of Style (16th Edition):

Arefiyan Khalilabad, Seyyed Mostafa. “Deep Learning Models for Context-Aware Object Detection.” 2017. Masters Thesis, Virginia Tech. Accessed October 21, 2020. http://hdl.handle.net/10919/88387.

MLA Handbook (7th Edition):

Arefiyan Khalilabad, Seyyed Mostafa. “Deep Learning Models for Context-Aware Object Detection.” 2017. Web. 21 Oct 2020.

Vancouver:

Arefiyan Khalilabad SM. Deep Learning Models for Context-Aware Object Detection. [Internet] [Masters thesis]. Virginia Tech; 2017. [cited 2020 Oct 21]. Available from: http://hdl.handle.net/10919/88387.

Council of Science Editors:

Arefiyan Khalilabad SM. Deep Learning Models for Context-Aware Object Detection. [Masters Thesis]. Virginia Tech; 2017. Available from: http://hdl.handle.net/10919/88387


Virginia Tech

22. AlBahar, Badour A Sh A. Im2Vid: Future Video Prediction for Static Image Action Recognition.

Degree: MS, Computer Engineering, 2018, Virginia Tech

 Static image action recognition aims at identifying the action performed in a given image. Most existing static image action recognition approaches use high-level cues present… (more)

Subjects/Keywords: Human Action Recognition; Static Image Action Recognition; Video Action Recognition; Future Video Prediction

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APA (6th Edition):

AlBahar, B. A. S. A. (2018). Im2Vid: Future Video Prediction for Static Image Action Recognition. (Masters Thesis). Virginia Tech. Retrieved from http://hdl.handle.net/10919/83602

Chicago Manual of Style (16th Edition):

AlBahar, Badour A Sh A. “Im2Vid: Future Video Prediction for Static Image Action Recognition.” 2018. Masters Thesis, Virginia Tech. Accessed October 21, 2020. http://hdl.handle.net/10919/83602.

MLA Handbook (7th Edition):

AlBahar, Badour A Sh A. “Im2Vid: Future Video Prediction for Static Image Action Recognition.” 2018. Web. 21 Oct 2020.

Vancouver:

AlBahar BASA. Im2Vid: Future Video Prediction for Static Image Action Recognition. [Internet] [Masters thesis]. Virginia Tech; 2018. [cited 2020 Oct 21]. Available from: http://hdl.handle.net/10919/83602.

Council of Science Editors:

AlBahar BASA. Im2Vid: Future Video Prediction for Static Image Action Recognition. [Masters Thesis]. Virginia Tech; 2018. Available from: http://hdl.handle.net/10919/83602


Virginia Tech

23. Delport, Jacques. Synchronized Measurement of Machine Rotor Angle and Its Application.

Degree: MS, Electrical Engineering, 2015, Virginia Tech

 The internal voltage angle of a generator is an important parameter that indicates the stability, both transient and steady-state, of the generator. This paper proposes… (more)

Subjects/Keywords: Rotor Angle; Synchronization; Power System Stabilizer

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APA (6th Edition):

Delport, J. (2015). Synchronized Measurement of Machine Rotor Angle and Its Application. (Masters Thesis). Virginia Tech. Retrieved from http://hdl.handle.net/10919/51242

Chicago Manual of Style (16th Edition):

Delport, Jacques. “Synchronized Measurement of Machine Rotor Angle and Its Application.” 2015. Masters Thesis, Virginia Tech. Accessed October 21, 2020. http://hdl.handle.net/10919/51242.

MLA Handbook (7th Edition):

Delport, Jacques. “Synchronized Measurement of Machine Rotor Angle and Its Application.” 2015. Web. 21 Oct 2020.

Vancouver:

Delport J. Synchronized Measurement of Machine Rotor Angle and Its Application. [Internet] [Masters thesis]. Virginia Tech; 2015. [cited 2020 Oct 21]. Available from: http://hdl.handle.net/10919/51242.

Council of Science Editors:

Delport J. Synchronized Measurement of Machine Rotor Angle and Its Application. [Masters Thesis]. Virginia Tech; 2015. Available from: http://hdl.handle.net/10919/51242


Virginia Tech

24. Chadha, Abhimanyu. Vision Based Localization of Drones in a GPS Denied Environment.

Degree: MS, Computer Engineering, 2020, Virginia Tech

 In the recent years, technologies like Deep Learning and Machine Learning have seen many rapid developments. This has lead to the rise of fields such… (more)

Subjects/Keywords: Autonomous UAVs; Stereovision; Localization

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APA (6th Edition):

Chadha, A. (2020). Vision Based Localization of Drones in a GPS Denied Environment. (Masters Thesis). Virginia Tech. Retrieved from http://hdl.handle.net/10919/99887

Chicago Manual of Style (16th Edition):

Chadha, Abhimanyu. “Vision Based Localization of Drones in a GPS Denied Environment.” 2020. Masters Thesis, Virginia Tech. Accessed October 21, 2020. http://hdl.handle.net/10919/99887.

MLA Handbook (7th Edition):

Chadha, Abhimanyu. “Vision Based Localization of Drones in a GPS Denied Environment.” 2020. Web. 21 Oct 2020.

Vancouver:

Chadha A. Vision Based Localization of Drones in a GPS Denied Environment. [Internet] [Masters thesis]. Virginia Tech; 2020. [cited 2020 Oct 21]. Available from: http://hdl.handle.net/10919/99887.

Council of Science Editors:

Chadha A. Vision Based Localization of Drones in a GPS Denied Environment. [Masters Thesis]. Virginia Tech; 2020. Available from: http://hdl.handle.net/10919/99887


Virginia Tech

25. Ray, Arijit. The Art of Deep Connection - Towards Natural and Pragmatic Conversational Agent Interactions.

Degree: MS, Computer Engineering, 2017, Virginia Tech

 As research in Artificial Intelligence (AI) advances, it is crucial to focus on having seamless communication between humans and machines in order to effectively accomplish… (more)

Subjects/Keywords: Computer Vision; Natural Language Processing; Conversational Agents; Chatbots; Deep Learning; Machine Learning; Artificial Intelligence

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APA (6th Edition):

Ray, A. (2017). The Art of Deep Connection - Towards Natural and Pragmatic Conversational Agent Interactions. (Masters Thesis). Virginia Tech. Retrieved from http://hdl.handle.net/10919/78335

Chicago Manual of Style (16th Edition):

Ray, Arijit. “The Art of Deep Connection - Towards Natural and Pragmatic Conversational Agent Interactions.” 2017. Masters Thesis, Virginia Tech. Accessed October 21, 2020. http://hdl.handle.net/10919/78335.

MLA Handbook (7th Edition):

Ray, Arijit. “The Art of Deep Connection - Towards Natural and Pragmatic Conversational Agent Interactions.” 2017. Web. 21 Oct 2020.

Vancouver:

Ray A. The Art of Deep Connection - Towards Natural and Pragmatic Conversational Agent Interactions. [Internet] [Masters thesis]. Virginia Tech; 2017. [cited 2020 Oct 21]. Available from: http://hdl.handle.net/10919/78335.

Council of Science Editors:

Ray A. The Art of Deep Connection - Towards Natural and Pragmatic Conversational Agent Interactions. [Masters Thesis]. Virginia Tech; 2017. Available from: http://hdl.handle.net/10919/78335


Virginia Tech

26. Agrawal, Harsh. CloudCV: Deep Learning and Computer Vision on the Cloud.

Degree: MS, Computer Engineering, 2016, Virginia Tech

 We are witnessing a proliferation of massive visual data. Visual content is arguably the fastest growing data on the web. Photo-sharing websites like Flickr and… (more)

Subjects/Keywords: Deep Learning; Computer Vision; Cloud Computing

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APA (6th Edition):

Agrawal, H. (2016). CloudCV: Deep Learning and Computer Vision on the Cloud. (Masters Thesis). Virginia Tech. Retrieved from http://hdl.handle.net/10919/71381

Chicago Manual of Style (16th Edition):

Agrawal, Harsh. “CloudCV: Deep Learning and Computer Vision on the Cloud.” 2016. Masters Thesis, Virginia Tech. Accessed October 21, 2020. http://hdl.handle.net/10919/71381.

MLA Handbook (7th Edition):

Agrawal, Harsh. “CloudCV: Deep Learning and Computer Vision on the Cloud.” 2016. Web. 21 Oct 2020.

Vancouver:

Agrawal H. CloudCV: Deep Learning and Computer Vision on the Cloud. [Internet] [Masters thesis]. Virginia Tech; 2016. [cited 2020 Oct 21]. Available from: http://hdl.handle.net/10919/71381.

Council of Science Editors:

Agrawal H. CloudCV: Deep Learning and Computer Vision on the Cloud. [Masters Thesis]. Virginia Tech; 2016. Available from: http://hdl.handle.net/10919/71381


Virginia Tech

27. Bansal, Kunal. Increasing Branch Coverage with Dual Metric RTL Test Generation.

Degree: MS, Computer Engineering, 2018, Virginia Tech

 In this thesis, we present a new register-transfer level (RTL) test generation method that makes use of two coverage metrics, Branch Coverage, and Mutation Coverage… (more)

Subjects/Keywords: Branch; Mutation; Coverage; Metric; RTL

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APA (6th Edition):

Bansal, K. (2018). Increasing Branch Coverage with Dual Metric RTL Test Generation. (Masters Thesis). Virginia Tech. Retrieved from http://hdl.handle.net/10919/96581

Chicago Manual of Style (16th Edition):

Bansal, Kunal. “Increasing Branch Coverage with Dual Metric RTL Test Generation.” 2018. Masters Thesis, Virginia Tech. Accessed October 21, 2020. http://hdl.handle.net/10919/96581.

MLA Handbook (7th Edition):

Bansal, Kunal. “Increasing Branch Coverage with Dual Metric RTL Test Generation.” 2018. Web. 21 Oct 2020.

Vancouver:

Bansal K. Increasing Branch Coverage with Dual Metric RTL Test Generation. [Internet] [Masters thesis]. Virginia Tech; 2018. [cited 2020 Oct 21]. Available from: http://hdl.handle.net/10919/96581.

Council of Science Editors:

Bansal K. Increasing Branch Coverage with Dual Metric RTL Test Generation. [Masters Thesis]. Virginia Tech; 2018. Available from: http://hdl.handle.net/10919/96581


Virginia Tech

28. Gaddam, Shravya. Design and Implementation of PUF Based Protocols for Remote Integrity Verification.

Degree: MS, Computer Engineering, 2016, Virginia Tech

 In recent years, there has been a drastic increase in the prevalence of counterfeiting within the electronics supply chain. At the same time, high-end commercial… (more)

Subjects/Keywords: Physical Unclonable Functions; ECDSA; Elliptic Curve Cryptography; Fuzzy Extraction; Strong Extraction

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APA (6th Edition):

Gaddam, S. (2016). Design and Implementation of PUF Based Protocols for Remote Integrity Verification. (Masters Thesis). Virginia Tech. Retrieved from http://hdl.handle.net/10919/71865

Chicago Manual of Style (16th Edition):

Gaddam, Shravya. “Design and Implementation of PUF Based Protocols for Remote Integrity Verification.” 2016. Masters Thesis, Virginia Tech. Accessed October 21, 2020. http://hdl.handle.net/10919/71865.

MLA Handbook (7th Edition):

Gaddam, Shravya. “Design and Implementation of PUF Based Protocols for Remote Integrity Verification.” 2016. Web. 21 Oct 2020.

Vancouver:

Gaddam S. Design and Implementation of PUF Based Protocols for Remote Integrity Verification. [Internet] [Masters thesis]. Virginia Tech; 2016. [cited 2020 Oct 21]. Available from: http://hdl.handle.net/10919/71865.

Council of Science Editors:

Gaddam S. Design and Implementation of PUF Based Protocols for Remote Integrity Verification. [Masters Thesis]. Virginia Tech; 2016. Available from: http://hdl.handle.net/10919/71865


Virginia Tech

29. Harekoppa, Pooja Puttaswamygowda. Application of Computer Vision Techniques for Railroad Inspection using UAVs.

Degree: MS, Computer Engineering, 2016, Virginia Tech

 The task of railroad inspection is a tedious one. It requires a lot of skilled experts and long hours of frequent on-field inspection. Automated ground… (more)

Subjects/Keywords: Computer Vision; Machine Learning; Railroad inspection; Unmanned Aerial Vehicle (UAV)

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APA (6th Edition):

Harekoppa, P. P. (2016). Application of Computer Vision Techniques for Railroad Inspection using UAVs. (Masters Thesis). Virginia Tech. Retrieved from http://hdl.handle.net/10919/72273

Chicago Manual of Style (16th Edition):

Harekoppa, Pooja Puttaswamygowda. “Application of Computer Vision Techniques for Railroad Inspection using UAVs.” 2016. Masters Thesis, Virginia Tech. Accessed October 21, 2020. http://hdl.handle.net/10919/72273.

MLA Handbook (7th Edition):

Harekoppa, Pooja Puttaswamygowda. “Application of Computer Vision Techniques for Railroad Inspection using UAVs.” 2016. Web. 21 Oct 2020.

Vancouver:

Harekoppa PP. Application of Computer Vision Techniques for Railroad Inspection using UAVs. [Internet] [Masters thesis]. Virginia Tech; 2016. [cited 2020 Oct 21]. Available from: http://hdl.handle.net/10919/72273.

Council of Science Editors:

Harekoppa PP. Application of Computer Vision Techniques for Railroad Inspection using UAVs. [Masters Thesis]. Virginia Tech; 2016. Available from: http://hdl.handle.net/10919/72273


Virginia Tech

30. DiMarco, Peter Lewis. Evaluation of Moving Target IPv6 Defense and Distributed Denial of Service Defenses.

Degree: MS, Computer Engineering, 2013, Virginia Tech

 A Denial-of-Service (DoS) attack is a network attack from a single machine that attempts to prevent the victim, the targeted machine, from communicating to other… (more)

Subjects/Keywords: IPv6; DDoS; Security

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APA (6th Edition):

DiMarco, P. L. (2013). Evaluation of Moving Target IPv6 Defense and Distributed Denial of Service Defenses. (Masters Thesis). Virginia Tech. Retrieved from http://hdl.handle.net/10919/24697

Chicago Manual of Style (16th Edition):

DiMarco, Peter Lewis. “Evaluation of Moving Target IPv6 Defense and Distributed Denial of Service Defenses.” 2013. Masters Thesis, Virginia Tech. Accessed October 21, 2020. http://hdl.handle.net/10919/24697.

MLA Handbook (7th Edition):

DiMarco, Peter Lewis. “Evaluation of Moving Target IPv6 Defense and Distributed Denial of Service Defenses.” 2013. Web. 21 Oct 2020.

Vancouver:

DiMarco PL. Evaluation of Moving Target IPv6 Defense and Distributed Denial of Service Defenses. [Internet] [Masters thesis]. Virginia Tech; 2013. [cited 2020 Oct 21]. Available from: http://hdl.handle.net/10919/24697.

Council of Science Editors:

DiMarco PL. Evaluation of Moving Target IPv6 Defense and Distributed Denial of Service Defenses. [Masters Thesis]. Virginia Tech; 2013. Available from: http://hdl.handle.net/10919/24697

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