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You searched for +publisher:"San Jose State University" +contributor:("Robert Chun"). Showing records 1 – 30 of 110 total matches.

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San Jose State University

1. Chokshi, Shirali. Video Chat Application for Facebook.

Degree: MS, Computer Science, 2011, San Jose State University

  This project is mainly written for the facebook users. In today’s world, there are many social networking sites available. Among those social networking web… (more)

Subjects/Keywords: video chat; Other Computer Sciences; Software Engineering

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APA (6th Edition):

Chokshi, S. (2011). Video Chat Application for Facebook. (Masters Thesis). San Jose State University. Retrieved from https://doi.org/10.31979/etd.cr2h-svuk ; https://scholarworks.sjsu.edu/etd_projects/186

Chicago Manual of Style (16th Edition):

Chokshi, Shirali. “Video Chat Application for Facebook.” 2011. Masters Thesis, San Jose State University. Accessed April 03, 2020. https://doi.org/10.31979/etd.cr2h-svuk ; https://scholarworks.sjsu.edu/etd_projects/186.

MLA Handbook (7th Edition):

Chokshi, Shirali. “Video Chat Application for Facebook.” 2011. Web. 03 Apr 2020.

Vancouver:

Chokshi S. Video Chat Application for Facebook. [Internet] [Masters thesis]. San Jose State University; 2011. [cited 2020 Apr 03]. Available from: https://doi.org/10.31979/etd.cr2h-svuk ; https://scholarworks.sjsu.edu/etd_projects/186.

Council of Science Editors:

Chokshi S. Video Chat Application for Facebook. [Masters Thesis]. San Jose State University; 2011. Available from: https://doi.org/10.31979/etd.cr2h-svuk ; https://scholarworks.sjsu.edu/etd_projects/186


San Jose State University

2. Mithe, Saurabh. Deep Learning on Graphs using Graph Convolutional Networks.

Degree: MS, Computer Science, 2019, San Jose State University

  Graphs are a powerful way to model network data with the objects as nodes and the relationship between the various objects as links. Such… (more)

Subjects/Keywords: Node embedding; machine learning; graph convolutional net- work; node classification.; Artificial Intelligence and Robotics; Theory and Algorithms

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APA (6th Edition):

Mithe, S. (2019). Deep Learning on Graphs using Graph Convolutional Networks. (Masters Thesis). San Jose State University. Retrieved from https://doi.org/10.31979/etd.yca4-fmqh ; https://scholarworks.sjsu.edu/etd_projects/720

Chicago Manual of Style (16th Edition):

Mithe, Saurabh. “Deep Learning on Graphs using Graph Convolutional Networks.” 2019. Masters Thesis, San Jose State University. Accessed April 03, 2020. https://doi.org/10.31979/etd.yca4-fmqh ; https://scholarworks.sjsu.edu/etd_projects/720.

MLA Handbook (7th Edition):

Mithe, Saurabh. “Deep Learning on Graphs using Graph Convolutional Networks.” 2019. Web. 03 Apr 2020.

Vancouver:

Mithe S. Deep Learning on Graphs using Graph Convolutional Networks. [Internet] [Masters thesis]. San Jose State University; 2019. [cited 2020 Apr 03]. Available from: https://doi.org/10.31979/etd.yca4-fmqh ; https://scholarworks.sjsu.edu/etd_projects/720.

Council of Science Editors:

Mithe S. Deep Learning on Graphs using Graph Convolutional Networks. [Masters Thesis]. San Jose State University; 2019. Available from: https://doi.org/10.31979/etd.yca4-fmqh ; https://scholarworks.sjsu.edu/etd_projects/720


San Jose State University

3. Gunaseelan, Saravana. SENTIMENT ANALYSIS FOR SEARCH ENGINE.

Degree: MS, Computer Science, 2019, San Jose State University

  The chief purpose of this study is to detect and eliminate the sentiment bias in a search engine. Sentiment bias means a bias induced… (more)

Subjects/Keywords: sentiment bias; search results; LSTM model; word embeddings; Artificial Intelligence and Robotics; Databases and Information Systems

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APA (6th Edition):

Gunaseelan, S. (2019). SENTIMENT ANALYSIS FOR SEARCH ENGINE. (Masters Thesis). San Jose State University. Retrieved from https://doi.org/10.31979/etd.fetx-v3gr ; https://scholarworks.sjsu.edu/etd_projects/694

Chicago Manual of Style (16th Edition):

Gunaseelan, Saravana. “SENTIMENT ANALYSIS FOR SEARCH ENGINE.” 2019. Masters Thesis, San Jose State University. Accessed April 03, 2020. https://doi.org/10.31979/etd.fetx-v3gr ; https://scholarworks.sjsu.edu/etd_projects/694.

MLA Handbook (7th Edition):

Gunaseelan, Saravana. “SENTIMENT ANALYSIS FOR SEARCH ENGINE.” 2019. Web. 03 Apr 2020.

Vancouver:

Gunaseelan S. SENTIMENT ANALYSIS FOR SEARCH ENGINE. [Internet] [Masters thesis]. San Jose State University; 2019. [cited 2020 Apr 03]. Available from: https://doi.org/10.31979/etd.fetx-v3gr ; https://scholarworks.sjsu.edu/etd_projects/694.

Council of Science Editors:

Gunaseelan S. SENTIMENT ANALYSIS FOR SEARCH ENGINE. [Masters Thesis]. San Jose State University; 2019. Available from: https://doi.org/10.31979/etd.fetx-v3gr ; https://scholarworks.sjsu.edu/etd_projects/694

4. Khanuja, Rashmeet Kaur. Optimizing E-Commerce Product Classification Using Transfer Learning.

Degree: MS, Computer Science, 2019, San Jose State University

  The global e-commerce market is snowballing at a rate of 23% per year. In 2017, retail e-commerce users were 1.66 billion and sales worldwide… (more)

Subjects/Keywords: convolutional neural networks; deep learning; dropout; e-commerce product categorization; keras; transfer learning; Artificial Intelligence and Robotics

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APA (6th Edition):

Khanuja, R. K. (2019). Optimizing E-Commerce Product Classification Using Transfer Learning. (Masters Thesis). San Jose State University. Retrieved from https://doi.org/10.31979/etd.egyw-ktc5 ; https://scholarworks.sjsu.edu/etd_projects/679

Chicago Manual of Style (16th Edition):

Khanuja, Rashmeet Kaur. “Optimizing E-Commerce Product Classification Using Transfer Learning.” 2019. Masters Thesis, San Jose State University. Accessed April 03, 2020. https://doi.org/10.31979/etd.egyw-ktc5 ; https://scholarworks.sjsu.edu/etd_projects/679.

MLA Handbook (7th Edition):

Khanuja, Rashmeet Kaur. “Optimizing E-Commerce Product Classification Using Transfer Learning.” 2019. Web. 03 Apr 2020.

Vancouver:

Khanuja RK. Optimizing E-Commerce Product Classification Using Transfer Learning. [Internet] [Masters thesis]. San Jose State University; 2019. [cited 2020 Apr 03]. Available from: https://doi.org/10.31979/etd.egyw-ktc5 ; https://scholarworks.sjsu.edu/etd_projects/679.

Council of Science Editors:

Khanuja RK. Optimizing E-Commerce Product Classification Using Transfer Learning. [Masters Thesis]. San Jose State University; 2019. Available from: https://doi.org/10.31979/etd.egyw-ktc5 ; https://scholarworks.sjsu.edu/etd_projects/679


San Jose State University

5. Mishra, Sonali. SQL Injection Detection Using Machine Learning.

Degree: MS, Computer Science, 2019, San Jose State University

  Sharing information over the Internet over multiple platforms and web-applications has become a quite common phenomenon in the recent times. The web-based applications that… (more)

Subjects/Keywords: SQL Injection Attack; Machine Learning Classifier; Artificial Intelligence and Robotics; Information Security

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APA (6th Edition):

Mishra, S. (2019). SQL Injection Detection Using Machine Learning. (Masters Thesis). San Jose State University. Retrieved from https://doi.org/10.31979/etd.j5dj-ngvb ; https://scholarworks.sjsu.edu/etd_projects/727

Chicago Manual of Style (16th Edition):

Mishra, Sonali. “SQL Injection Detection Using Machine Learning.” 2019. Masters Thesis, San Jose State University. Accessed April 03, 2020. https://doi.org/10.31979/etd.j5dj-ngvb ; https://scholarworks.sjsu.edu/etd_projects/727.

MLA Handbook (7th Edition):

Mishra, Sonali. “SQL Injection Detection Using Machine Learning.” 2019. Web. 03 Apr 2020.

Vancouver:

Mishra S. SQL Injection Detection Using Machine Learning. [Internet] [Masters thesis]. San Jose State University; 2019. [cited 2020 Apr 03]. Available from: https://doi.org/10.31979/etd.j5dj-ngvb ; https://scholarworks.sjsu.edu/etd_projects/727.

Council of Science Editors:

Mishra S. SQL Injection Detection Using Machine Learning. [Masters Thesis]. San Jose State University; 2019. Available from: https://doi.org/10.31979/etd.j5dj-ngvb ; https://scholarworks.sjsu.edu/etd_projects/727


San Jose State University

6. Patira, Samkit. Over speed detection using Artificial Intelligence.

Degree: MS, Computer Science, 2019, San Jose State University

  Over speeding is one of the most common traffic violations. Around 41 million people are issued speeding tickets each year in USA i.e one… (more)

Subjects/Keywords: speeding; computer vision; YOLO; Artificial Intelligence and Robotics

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APA (6th Edition):

Patira, S. (2019). Over speed detection using Artificial Intelligence. (Masters Thesis). San Jose State University. Retrieved from https://doi.org/10.31979/etd.u8qc-9d6e ; https://scholarworks.sjsu.edu/etd_projects/712

Chicago Manual of Style (16th Edition):

Patira, Samkit. “Over speed detection using Artificial Intelligence.” 2019. Masters Thesis, San Jose State University. Accessed April 03, 2020. https://doi.org/10.31979/etd.u8qc-9d6e ; https://scholarworks.sjsu.edu/etd_projects/712.

MLA Handbook (7th Edition):

Patira, Samkit. “Over speed detection using Artificial Intelligence.” 2019. Web. 03 Apr 2020.

Vancouver:

Patira S. Over speed detection using Artificial Intelligence. [Internet] [Masters thesis]. San Jose State University; 2019. [cited 2020 Apr 03]. Available from: https://doi.org/10.31979/etd.u8qc-9d6e ; https://scholarworks.sjsu.edu/etd_projects/712.

Council of Science Editors:

Patira S. Over speed detection using Artificial Intelligence. [Masters Thesis]. San Jose State University; 2019. Available from: https://doi.org/10.31979/etd.u8qc-9d6e ; https://scholarworks.sjsu.edu/etd_projects/712


San Jose State University

7. Chhabra, Aseem. Deep Learning Based Real Time Devanagari Character Recognition.

Degree: MS, Computer Science, 2019, San Jose State University

  The revolutionization of the technology behind optical character recognition (OCR) has helped it to become one of those technologies that have found plenty of… (more)

Subjects/Keywords: Optical Character Recognition; Artificial Intelligence; Deep Neural Network; Deep Learning; Devanagari Script; Artificial Intelligence and Robotics

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APA (6th Edition):

Chhabra, A. (2019). Deep Learning Based Real Time Devanagari Character Recognition. (Masters Thesis). San Jose State University. Retrieved from https://doi.org/10.31979/etd.3yh5-xs5s ; https://scholarworks.sjsu.edu/etd_projects/717

Chicago Manual of Style (16th Edition):

Chhabra, Aseem. “Deep Learning Based Real Time Devanagari Character Recognition.” 2019. Masters Thesis, San Jose State University. Accessed April 03, 2020. https://doi.org/10.31979/etd.3yh5-xs5s ; https://scholarworks.sjsu.edu/etd_projects/717.

MLA Handbook (7th Edition):

Chhabra, Aseem. “Deep Learning Based Real Time Devanagari Character Recognition.” 2019. Web. 03 Apr 2020.

Vancouver:

Chhabra A. Deep Learning Based Real Time Devanagari Character Recognition. [Internet] [Masters thesis]. San Jose State University; 2019. [cited 2020 Apr 03]. Available from: https://doi.org/10.31979/etd.3yh5-xs5s ; https://scholarworks.sjsu.edu/etd_projects/717.

Council of Science Editors:

Chhabra A. Deep Learning Based Real Time Devanagari Character Recognition. [Masters Thesis]. San Jose State University; 2019. Available from: https://doi.org/10.31979/etd.3yh5-xs5s ; https://scholarworks.sjsu.edu/etd_projects/717


San Jose State University

8. Pachpute, Shubham Shashishekhar. Malware Analysis on PDF.

Degree: MS, Computer Science, 2019, San Jose State University

  Cyber-attacks are growing day by day and attackers are finding new techniques to cause harm to their target by spreading worms and malware. In… (more)

Subjects/Keywords: cyber-attacks; malware; Portable Document Format (PDF); Information Security

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APA (6th Edition):

Pachpute, S. S. (2019). Malware Analysis on PDF. (Masters Thesis). San Jose State University. Retrieved from https://doi.org/10.31979/etd.pf8d-htjh ; https://scholarworks.sjsu.edu/etd_projects/683

Chicago Manual of Style (16th Edition):

Pachpute, Shubham Shashishekhar. “Malware Analysis on PDF.” 2019. Masters Thesis, San Jose State University. Accessed April 03, 2020. https://doi.org/10.31979/etd.pf8d-htjh ; https://scholarworks.sjsu.edu/etd_projects/683.

MLA Handbook (7th Edition):

Pachpute, Shubham Shashishekhar. “Malware Analysis on PDF.” 2019. Web. 03 Apr 2020.

Vancouver:

Pachpute SS. Malware Analysis on PDF. [Internet] [Masters thesis]. San Jose State University; 2019. [cited 2020 Apr 03]. Available from: https://doi.org/10.31979/etd.pf8d-htjh ; https://scholarworks.sjsu.edu/etd_projects/683.

Council of Science Editors:

Pachpute SS. Malware Analysis on PDF. [Masters Thesis]. San Jose State University; 2019. Available from: https://doi.org/10.31979/etd.pf8d-htjh ; https://scholarworks.sjsu.edu/etd_projects/683


San Jose State University

9. Bhandary, Unnathi. Detection of Hate Speech in Videos Using Machine Learning.

Degree: MS, Computer Science, 2019, San Jose State University

  With the progression of the internet and social media, people are given multiple platforms to share their thoughts and opinions about various subject matters… (more)

Subjects/Keywords: hate speech detector; cyber bullying; random forest classifier; Artificial Intelligence and Robotics

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APA (6th Edition):

Bhandary, U. (2019). Detection of Hate Speech in Videos Using Machine Learning. (Masters Thesis). San Jose State University. Retrieved from https://doi.org/10.31979/etd.5efp-73s4 ; https://scholarworks.sjsu.edu/etd_projects/691

Chicago Manual of Style (16th Edition):

Bhandary, Unnathi. “Detection of Hate Speech in Videos Using Machine Learning.” 2019. Masters Thesis, San Jose State University. Accessed April 03, 2020. https://doi.org/10.31979/etd.5efp-73s4 ; https://scholarworks.sjsu.edu/etd_projects/691.

MLA Handbook (7th Edition):

Bhandary, Unnathi. “Detection of Hate Speech in Videos Using Machine Learning.” 2019. Web. 03 Apr 2020.

Vancouver:

Bhandary U. Detection of Hate Speech in Videos Using Machine Learning. [Internet] [Masters thesis]. San Jose State University; 2019. [cited 2020 Apr 03]. Available from: https://doi.org/10.31979/etd.5efp-73s4 ; https://scholarworks.sjsu.edu/etd_projects/691.

Council of Science Editors:

Bhandary U. Detection of Hate Speech in Videos Using Machine Learning. [Masters Thesis]. San Jose State University; 2019. Available from: https://doi.org/10.31979/etd.5efp-73s4 ; https://scholarworks.sjsu.edu/etd_projects/691


San Jose State University

10. Nguyen, David. Randition: Random Blockchain Partitioning for Write Throughput.

Degree: MS, Computer Science, 2019, San Jose State University

  This paper proposes to support dynamic runtime partitioning of Tendermint, which is an in-development state machine replication algorithm that uses the blockchain model to… (more)

Subjects/Keywords: Other Computer Sciences

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APA (6th Edition):

Nguyen, D. (2019). Randition: Random Blockchain Partitioning for Write Throughput. (Masters Thesis). San Jose State University. Retrieved from https://doi.org/10.31979/etd.7x8u-mhyr ; https://scholarworks.sjsu.edu/etd_projects/731

Chicago Manual of Style (16th Edition):

Nguyen, David. “Randition: Random Blockchain Partitioning for Write Throughput.” 2019. Masters Thesis, San Jose State University. Accessed April 03, 2020. https://doi.org/10.31979/etd.7x8u-mhyr ; https://scholarworks.sjsu.edu/etd_projects/731.

MLA Handbook (7th Edition):

Nguyen, David. “Randition: Random Blockchain Partitioning for Write Throughput.” 2019. Web. 03 Apr 2020.

Vancouver:

Nguyen D. Randition: Random Blockchain Partitioning for Write Throughput. [Internet] [Masters thesis]. San Jose State University; 2019. [cited 2020 Apr 03]. Available from: https://doi.org/10.31979/etd.7x8u-mhyr ; https://scholarworks.sjsu.edu/etd_projects/731.

Council of Science Editors:

Nguyen D. Randition: Random Blockchain Partitioning for Write Throughput. [Masters Thesis]. San Jose State University; 2019. Available from: https://doi.org/10.31979/etd.7x8u-mhyr ; https://scholarworks.sjsu.edu/etd_projects/731


San Jose State University

11. Kulkarni, Siddharth. YODA – Your Only Design Assistant.

Degree: MS, Computer Science, 2019, San Jose State University

  Converting user interface designs created by graphic designers into computer code is a typical job of a front end engineer in order to develop… (more)

Subjects/Keywords: Artificial Intelligence (AI); machine learning (ML); user interface (UI); Convolutional Neural Networks (CNN); Artificial Intelligence and Robotics; Graphics and Human Computer Interfaces

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APA (6th Edition):

Kulkarni, S. (2019). YODA – Your Only Design Assistant. (Masters Thesis). San Jose State University. Retrieved from https://doi.org/10.31979/etd.cgjn-k7t4 ; https://scholarworks.sjsu.edu/etd_projects/728

Chicago Manual of Style (16th Edition):

Kulkarni, Siddharth. “YODA – Your Only Design Assistant.” 2019. Masters Thesis, San Jose State University. Accessed April 03, 2020. https://doi.org/10.31979/etd.cgjn-k7t4 ; https://scholarworks.sjsu.edu/etd_projects/728.

MLA Handbook (7th Edition):

Kulkarni, Siddharth. “YODA – Your Only Design Assistant.” 2019. Web. 03 Apr 2020.

Vancouver:

Kulkarni S. YODA – Your Only Design Assistant. [Internet] [Masters thesis]. San Jose State University; 2019. [cited 2020 Apr 03]. Available from: https://doi.org/10.31979/etd.cgjn-k7t4 ; https://scholarworks.sjsu.edu/etd_projects/728.

Council of Science Editors:

Kulkarni S. YODA – Your Only Design Assistant. [Masters Thesis]. San Jose State University; 2019. Available from: https://doi.org/10.31979/etd.cgjn-k7t4 ; https://scholarworks.sjsu.edu/etd_projects/728


San Jose State University

12. Fowler, Colin M. CONTRACT BUILDER ETHEREUM APPLICATION.

Degree: MS, Computer Science, 2019, San Jose State University

  Developments in Blockchain, smart contract, and decentralized application (“dApps”) technology have enabled new types of software that can improve efficiency within law firms by… (more)

Subjects/Keywords: Smart Contracts; blockchain; Information Security; Other Computer Sciences

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APA (6th Edition):

Fowler, C. M. (2019). CONTRACT BUILDER ETHEREUM APPLICATION. (Masters Thesis). San Jose State University. Retrieved from https://doi.org/10.31979/etd.mv6q-e9bp ; https://scholarworks.sjsu.edu/etd_projects/686

Chicago Manual of Style (16th Edition):

Fowler, Colin M. “CONTRACT BUILDER ETHEREUM APPLICATION.” 2019. Masters Thesis, San Jose State University. Accessed April 03, 2020. https://doi.org/10.31979/etd.mv6q-e9bp ; https://scholarworks.sjsu.edu/etd_projects/686.

MLA Handbook (7th Edition):

Fowler, Colin M. “CONTRACT BUILDER ETHEREUM APPLICATION.” 2019. Web. 03 Apr 2020.

Vancouver:

Fowler CM. CONTRACT BUILDER ETHEREUM APPLICATION. [Internet] [Masters thesis]. San Jose State University; 2019. [cited 2020 Apr 03]. Available from: https://doi.org/10.31979/etd.mv6q-e9bp ; https://scholarworks.sjsu.edu/etd_projects/686.

Council of Science Editors:

Fowler CM. CONTRACT BUILDER ETHEREUM APPLICATION. [Masters Thesis]. San Jose State University; 2019. Available from: https://doi.org/10.31979/etd.mv6q-e9bp ; https://scholarworks.sjsu.edu/etd_projects/686


San Jose State University

13. Seenappa, Monica Golahalli. Graph Classification using Machine Learning Algorithms.

Degree: MS, Computer Science, 2019, San Jose State University

  In the Graph classification problem, given is a family of graphs and a group of different categories, and we aim to classify all the… (more)

Subjects/Keywords: Graph Kernels; Convolutional Neural Network; Community detec- tion; Spectral decomposition; Artificial Intelligence and Robotics

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APA (6th Edition):

Seenappa, M. G. (2019). Graph Classification using Machine Learning Algorithms. (Masters Thesis). San Jose State University. Retrieved from https://doi.org/10.31979/etd.b9pm-wpng ; https://scholarworks.sjsu.edu/etd_projects/725

Chicago Manual of Style (16th Edition):

Seenappa, Monica Golahalli. “Graph Classification using Machine Learning Algorithms.” 2019. Masters Thesis, San Jose State University. Accessed April 03, 2020. https://doi.org/10.31979/etd.b9pm-wpng ; https://scholarworks.sjsu.edu/etd_projects/725.

MLA Handbook (7th Edition):

Seenappa, Monica Golahalli. “Graph Classification using Machine Learning Algorithms.” 2019. Web. 03 Apr 2020.

Vancouver:

Seenappa MG. Graph Classification using Machine Learning Algorithms. [Internet] [Masters thesis]. San Jose State University; 2019. [cited 2020 Apr 03]. Available from: https://doi.org/10.31979/etd.b9pm-wpng ; https://scholarworks.sjsu.edu/etd_projects/725.

Council of Science Editors:

Seenappa MG. Graph Classification using Machine Learning Algorithms. [Masters Thesis]. San Jose State University; 2019. Available from: https://doi.org/10.31979/etd.b9pm-wpng ; https://scholarworks.sjsu.edu/etd_projects/725


San Jose State University

14. Sharma, Abhishek Manoj. Speaker Recognition Using Machine Learning Techniques.

Degree: MS, Computer Science, 2019, San Jose State University

  Speaker recognition is a technique of identifying the person talking to a machine using the voice features and acoustics. It has multiple applications ranging… (more)

Subjects/Keywords: Speaker recognition; human computer interaction; biometrics; internet of things; mel frequency cepstral coefficients; Artificial Intelligence and Robotics

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APA (6th Edition):

Sharma, A. M. (2019). Speaker Recognition Using Machine Learning Techniques. (Masters Thesis). San Jose State University. Retrieved from https://doi.org/10.31979/etd.fhhr-49pm ; https://scholarworks.sjsu.edu/etd_projects/685

Chicago Manual of Style (16th Edition):

Sharma, Abhishek Manoj. “Speaker Recognition Using Machine Learning Techniques.” 2019. Masters Thesis, San Jose State University. Accessed April 03, 2020. https://doi.org/10.31979/etd.fhhr-49pm ; https://scholarworks.sjsu.edu/etd_projects/685.

MLA Handbook (7th Edition):

Sharma, Abhishek Manoj. “Speaker Recognition Using Machine Learning Techniques.” 2019. Web. 03 Apr 2020.

Vancouver:

Sharma AM. Speaker Recognition Using Machine Learning Techniques. [Internet] [Masters thesis]. San Jose State University; 2019. [cited 2020 Apr 03]. Available from: https://doi.org/10.31979/etd.fhhr-49pm ; https://scholarworks.sjsu.edu/etd_projects/685.

Council of Science Editors:

Sharma AM. Speaker Recognition Using Machine Learning Techniques. [Masters Thesis]. San Jose State University; 2019. Available from: https://doi.org/10.31979/etd.fhhr-49pm ; https://scholarworks.sjsu.edu/etd_projects/685


San Jose State University

15. Mahna, Shivanku. Improving Steering Ability of an Autopilot in a Fully Autonomous Car.

Degree: MS, Computer Science, 2019, San Jose State University

  The world we live in is developing at a really rapid pace and along with it is developing the technology that we use. We… (more)

Subjects/Keywords: autonomous cars; CNNs; Artificial Intelligence and Robotics

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APA (6th Edition):

Mahna, S. (2019). Improving Steering Ability of an Autopilot in a Fully Autonomous Car. (Masters Thesis). San Jose State University. Retrieved from https://doi.org/10.31979/etd.b9hs-3fce ; https://scholarworks.sjsu.edu/etd_projects/716

Chicago Manual of Style (16th Edition):

Mahna, Shivanku. “Improving Steering Ability of an Autopilot in a Fully Autonomous Car.” 2019. Masters Thesis, San Jose State University. Accessed April 03, 2020. https://doi.org/10.31979/etd.b9hs-3fce ; https://scholarworks.sjsu.edu/etd_projects/716.

MLA Handbook (7th Edition):

Mahna, Shivanku. “Improving Steering Ability of an Autopilot in a Fully Autonomous Car.” 2019. Web. 03 Apr 2020.

Vancouver:

Mahna S. Improving Steering Ability of an Autopilot in a Fully Autonomous Car. [Internet] [Masters thesis]. San Jose State University; 2019. [cited 2020 Apr 03]. Available from: https://doi.org/10.31979/etd.b9hs-3fce ; https://scholarworks.sjsu.edu/etd_projects/716.

Council of Science Editors:

Mahna S. Improving Steering Ability of an Autopilot in a Fully Autonomous Car. [Masters Thesis]. San Jose State University; 2019. Available from: https://doi.org/10.31979/etd.b9hs-3fce ; https://scholarworks.sjsu.edu/etd_projects/716


San Jose State University

16. Shelke, Jayant. TOPIC CLASSIFICATION USING HYBRID OF UNSUPERVISED AND SUPERVISED LEARNING.

Degree: MS, Computer Science, 2019, San Jose State University

  There has been research around the idea of representing words in text as vectors and many models proposed that vary in performance as well… (more)

Subjects/Keywords: opic detection; topic modeling; hybrid; topic mixtures; SVM; neural network; doc2vec; LDA.; Artificial Intelligence and Robotics; Databases and Information Systems

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APA (6th Edition):

Shelke, J. (2019). TOPIC CLASSIFICATION USING HYBRID OF UNSUPERVISED AND SUPERVISED LEARNING. (Masters Thesis). San Jose State University. Retrieved from https://doi.org/10.31979/etd.qvgp-5et8 ; https://scholarworks.sjsu.edu/etd_projects/693

Chicago Manual of Style (16th Edition):

Shelke, Jayant. “TOPIC CLASSIFICATION USING HYBRID OF UNSUPERVISED AND SUPERVISED LEARNING.” 2019. Masters Thesis, San Jose State University. Accessed April 03, 2020. https://doi.org/10.31979/etd.qvgp-5et8 ; https://scholarworks.sjsu.edu/etd_projects/693.

MLA Handbook (7th Edition):

Shelke, Jayant. “TOPIC CLASSIFICATION USING HYBRID OF UNSUPERVISED AND SUPERVISED LEARNING.” 2019. Web. 03 Apr 2020.

Vancouver:

Shelke J. TOPIC CLASSIFICATION USING HYBRID OF UNSUPERVISED AND SUPERVISED LEARNING. [Internet] [Masters thesis]. San Jose State University; 2019. [cited 2020 Apr 03]. Available from: https://doi.org/10.31979/etd.qvgp-5et8 ; https://scholarworks.sjsu.edu/etd_projects/693.

Council of Science Editors:

Shelke J. TOPIC CLASSIFICATION USING HYBRID OF UNSUPERVISED AND SUPERVISED LEARNING. [Masters Thesis]. San Jose State University; 2019. Available from: https://doi.org/10.31979/etd.qvgp-5et8 ; https://scholarworks.sjsu.edu/etd_projects/693


San Jose State University

17. Mullapudi, Krishna Chaitanya. Schema Migration from Relational Databases to NoSQL Databases with Graph Transformation and Selective Denormalization.

Degree: MS, Computer Science, 2019, San Jose State University

  We witnessed a dramatic increase in the volume, variety and velocity of data leading to the era of big data. The structure of data… (more)

Subjects/Keywords: Schema Migration; NoSqL; Databases and Information Systems

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APA (6th Edition):

Mullapudi, K. C. (2019). Schema Migration from Relational Databases to NoSQL Databases with Graph Transformation and Selective Denormalization. (Masters Thesis). San Jose State University. Retrieved from https://doi.org/10.31979/etd.x6s2-94xe ; https://scholarworks.sjsu.edu/etd_projects/714

Chicago Manual of Style (16th Edition):

Mullapudi, Krishna Chaitanya. “Schema Migration from Relational Databases to NoSQL Databases with Graph Transformation and Selective Denormalization.” 2019. Masters Thesis, San Jose State University. Accessed April 03, 2020. https://doi.org/10.31979/etd.x6s2-94xe ; https://scholarworks.sjsu.edu/etd_projects/714.

MLA Handbook (7th Edition):

Mullapudi, Krishna Chaitanya. “Schema Migration from Relational Databases to NoSQL Databases with Graph Transformation and Selective Denormalization.” 2019. Web. 03 Apr 2020.

Vancouver:

Mullapudi KC. Schema Migration from Relational Databases to NoSQL Databases with Graph Transformation and Selective Denormalization. [Internet] [Masters thesis]. San Jose State University; 2019. [cited 2020 Apr 03]. Available from: https://doi.org/10.31979/etd.x6s2-94xe ; https://scholarworks.sjsu.edu/etd_projects/714.

Council of Science Editors:

Mullapudi KC. Schema Migration from Relational Databases to NoSQL Databases with Graph Transformation and Selective Denormalization. [Masters Thesis]. San Jose State University; 2019. Available from: https://doi.org/10.31979/etd.x6s2-94xe ; https://scholarworks.sjsu.edu/etd_projects/714


San Jose State University

18. Nanjappan, Avinashilingam. R*-Tree index in Cassandra for Geospatial Processing.

Degree: MS, Computer Science, 2019, San Jose State University

  Geospatial data has garnered enough attention in recent times that it is being used everywhere right from simple applications such as booking a taxi… (more)

Subjects/Keywords: geospatial indexing; R-trees; Z-curve; Cassandra; GeoMesa; Computer Sciences

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APA (6th Edition):

Nanjappan, A. (2019). R*-Tree index in Cassandra for Geospatial Processing. (Masters Thesis). San Jose State University. Retrieved from https://doi.org/10.31979/etd.55t5-e77a ; https://scholarworks.sjsu.edu/etd_projects/713

Chicago Manual of Style (16th Edition):

Nanjappan, Avinashilingam. “R*-Tree index in Cassandra for Geospatial Processing.” 2019. Masters Thesis, San Jose State University. Accessed April 03, 2020. https://doi.org/10.31979/etd.55t5-e77a ; https://scholarworks.sjsu.edu/etd_projects/713.

MLA Handbook (7th Edition):

Nanjappan, Avinashilingam. “R*-Tree index in Cassandra for Geospatial Processing.” 2019. Web. 03 Apr 2020.

Vancouver:

Nanjappan A. R*-Tree index in Cassandra for Geospatial Processing. [Internet] [Masters thesis]. San Jose State University; 2019. [cited 2020 Apr 03]. Available from: https://doi.org/10.31979/etd.55t5-e77a ; https://scholarworks.sjsu.edu/etd_projects/713.

Council of Science Editors:

Nanjappan A. R*-Tree index in Cassandra for Geospatial Processing. [Masters Thesis]. San Jose State University; 2019. Available from: https://doi.org/10.31979/etd.55t5-e77a ; https://scholarworks.sjsu.edu/etd_projects/713


San Jose State University

19. Lahoti, Nikhil. Low Power MobileNets Acceleration In Cuda And OpenCL.

Degree: MS, Computer Science, 2019, San Jose State University

  Convolutional Neural Network (CNN) has been used widely for the tasks of object recognition and facial recognition because of their remarkable results on these… (more)

Subjects/Keywords: CNN; Benchmark Suite; Embedded devices; Cuda; OpenCL; Deep Neural Network; Artificial Intelligence and Robotics; Other Computer Sciences

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APA (6th Edition):

Lahoti, N. (2019). Low Power MobileNets Acceleration In Cuda And OpenCL. (Masters Thesis). San Jose State University. Retrieved from https://doi.org/10.31979/etd.5g5e-pvww ; https://scholarworks.sjsu.edu/etd_projects/680

Chicago Manual of Style (16th Edition):

Lahoti, Nikhil. “Low Power MobileNets Acceleration In Cuda And OpenCL.” 2019. Masters Thesis, San Jose State University. Accessed April 03, 2020. https://doi.org/10.31979/etd.5g5e-pvww ; https://scholarworks.sjsu.edu/etd_projects/680.

MLA Handbook (7th Edition):

Lahoti, Nikhil. “Low Power MobileNets Acceleration In Cuda And OpenCL.” 2019. Web. 03 Apr 2020.

Vancouver:

Lahoti N. Low Power MobileNets Acceleration In Cuda And OpenCL. [Internet] [Masters thesis]. San Jose State University; 2019. [cited 2020 Apr 03]. Available from: https://doi.org/10.31979/etd.5g5e-pvww ; https://scholarworks.sjsu.edu/etd_projects/680.

Council of Science Editors:

Lahoti N. Low Power MobileNets Acceleration In Cuda And OpenCL. [Masters Thesis]. San Jose State University; 2019. Available from: https://doi.org/10.31979/etd.5g5e-pvww ; https://scholarworks.sjsu.edu/etd_projects/680


San Jose State University

20. Narkhede, Anish Hemant. Human Activity Recognition Based on Multimodal Body Sensing.

Degree: MS, Computer Science, 2019, San Jose State University

  In the recent years, human activity recognition has been widely popularized by a lot of smartphone manufacturers and fitness tracking companies. It has allowed… (more)

Subjects/Keywords: Classification; dimensionality reduction; neural networks; human activity recognition; Artificial Intelligence and Robotics

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APA (6th Edition):

Narkhede, A. H. (2019). Human Activity Recognition Based on Multimodal Body Sensing. (Masters Thesis). San Jose State University. Retrieved from https://doi.org/10.31979/etd.zq8y-564m ; https://scholarworks.sjsu.edu/etd_projects/682

Chicago Manual of Style (16th Edition):

Narkhede, Anish Hemant. “Human Activity Recognition Based on Multimodal Body Sensing.” 2019. Masters Thesis, San Jose State University. Accessed April 03, 2020. https://doi.org/10.31979/etd.zq8y-564m ; https://scholarworks.sjsu.edu/etd_projects/682.

MLA Handbook (7th Edition):

Narkhede, Anish Hemant. “Human Activity Recognition Based on Multimodal Body Sensing.” 2019. Web. 03 Apr 2020.

Vancouver:

Narkhede AH. Human Activity Recognition Based on Multimodal Body Sensing. [Internet] [Masters thesis]. San Jose State University; 2019. [cited 2020 Apr 03]. Available from: https://doi.org/10.31979/etd.zq8y-564m ; https://scholarworks.sjsu.edu/etd_projects/682.

Council of Science Editors:

Narkhede AH. Human Activity Recognition Based on Multimodal Body Sensing. [Masters Thesis]. San Jose State University; 2019. Available from: https://doi.org/10.31979/etd.zq8y-564m ; https://scholarworks.sjsu.edu/etd_projects/682


San Jose State University

21. Badshah, Mustafa. Sensor - Based Human Activity Recognition Using Smartphones.

Degree: MS, Computer Science, 2019, San Jose State University

  It is a significant technical and computational task to provide precise information regarding the activity performed by a human and find patterns of their… (more)

Subjects/Keywords: Human activity recognition; machine learning; mobile sensors; accelerometer; gyroscope; feature selection; RNN; Artificial Intelligence and Robotics

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APA (6th Edition):

Badshah, M. (2019). Sensor - Based Human Activity Recognition Using Smartphones. (Masters Thesis). San Jose State University. Retrieved from https://doi.org/10.31979/etd.8fjc-drpn ; https://scholarworks.sjsu.edu/etd_projects/677

Chicago Manual of Style (16th Edition):

Badshah, Mustafa. “Sensor - Based Human Activity Recognition Using Smartphones.” 2019. Masters Thesis, San Jose State University. Accessed April 03, 2020. https://doi.org/10.31979/etd.8fjc-drpn ; https://scholarworks.sjsu.edu/etd_projects/677.

MLA Handbook (7th Edition):

Badshah, Mustafa. “Sensor - Based Human Activity Recognition Using Smartphones.” 2019. Web. 03 Apr 2020.

Vancouver:

Badshah M. Sensor - Based Human Activity Recognition Using Smartphones. [Internet] [Masters thesis]. San Jose State University; 2019. [cited 2020 Apr 03]. Available from: https://doi.org/10.31979/etd.8fjc-drpn ; https://scholarworks.sjsu.edu/etd_projects/677.

Council of Science Editors:

Badshah M. Sensor - Based Human Activity Recognition Using Smartphones. [Masters Thesis]. San Jose State University; 2019. Available from: https://doi.org/10.31979/etd.8fjc-drpn ; https://scholarworks.sjsu.edu/etd_projects/677


San Jose State University

22. Khieu, Brian Tuan. TSAR : A System for Defending Hate Speech Detection Models Against Adversaries.

Degree: MS, Computer Science, 2019, San Jose State University

  Although current state-of-the-art hate speech detection models achieve praiseworthy results, these models have shown themselves to be vulnerable to attack. Easy to execute lexical… (more)

Subjects/Keywords: hate speech detection; social networks; Artificial Intelligence and Robotics; Other Computer Sciences

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APA (6th Edition):

Khieu, B. T. (2019). TSAR : A System for Defending Hate Speech Detection Models Against Adversaries. (Masters Thesis). San Jose State University. Retrieved from https://doi.org/10.31979/etd.6tsk-redu ; https://scholarworks.sjsu.edu/etd_projects/740

Chicago Manual of Style (16th Edition):

Khieu, Brian Tuan. “TSAR : A System for Defending Hate Speech Detection Models Against Adversaries.” 2019. Masters Thesis, San Jose State University. Accessed April 03, 2020. https://doi.org/10.31979/etd.6tsk-redu ; https://scholarworks.sjsu.edu/etd_projects/740.

MLA Handbook (7th Edition):

Khieu, Brian Tuan. “TSAR : A System for Defending Hate Speech Detection Models Against Adversaries.” 2019. Web. 03 Apr 2020.

Vancouver:

Khieu BT. TSAR : A System for Defending Hate Speech Detection Models Against Adversaries. [Internet] [Masters thesis]. San Jose State University; 2019. [cited 2020 Apr 03]. Available from: https://doi.org/10.31979/etd.6tsk-redu ; https://scholarworks.sjsu.edu/etd_projects/740.

Council of Science Editors:

Khieu BT. TSAR : A System for Defending Hate Speech Detection Models Against Adversaries. [Masters Thesis]. San Jose State University; 2019. Available from: https://doi.org/10.31979/etd.6tsk-redu ; https://scholarworks.sjsu.edu/etd_projects/740


San Jose State University

23. Kanwar, Yuvraj Singh. Benchmarking Scalability of NoSQL Databases for Geospatial Queries.

Degree: MS, Computer Science, 2019, San Jose State University

  NoSQL databases provide an edge when it comes to dealing with big unstructured data. Flexibility, agility, and scalability offered by NoSQL databases become increasingly… (more)

Subjects/Keywords: Benchmarking; Couchbase; Geospatial Queries; MongoDB; NoSQL Databases; Performance Evaluation; Replication; Scalability; Databases and Information Systems

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APA (6th Edition):

Kanwar, Y. S. (2019). Benchmarking Scalability of NoSQL Databases for Geospatial Queries. (Masters Thesis). San Jose State University. Retrieved from https://doi.org/10.31979/etd.azm5-7asx ; https://scholarworks.sjsu.edu/etd_projects/673

Chicago Manual of Style (16th Edition):

Kanwar, Yuvraj Singh. “Benchmarking Scalability of NoSQL Databases for Geospatial Queries.” 2019. Masters Thesis, San Jose State University. Accessed April 03, 2020. https://doi.org/10.31979/etd.azm5-7asx ; https://scholarworks.sjsu.edu/etd_projects/673.

MLA Handbook (7th Edition):

Kanwar, Yuvraj Singh. “Benchmarking Scalability of NoSQL Databases for Geospatial Queries.” 2019. Web. 03 Apr 2020.

Vancouver:

Kanwar YS. Benchmarking Scalability of NoSQL Databases for Geospatial Queries. [Internet] [Masters thesis]. San Jose State University; 2019. [cited 2020 Apr 03]. Available from: https://doi.org/10.31979/etd.azm5-7asx ; https://scholarworks.sjsu.edu/etd_projects/673.

Council of Science Editors:

Kanwar YS. Benchmarking Scalability of NoSQL Databases for Geospatial Queries. [Masters Thesis]. San Jose State University; 2019. Available from: https://doi.org/10.31979/etd.azm5-7asx ; https://scholarworks.sjsu.edu/etd_projects/673


San Jose State University

24. Guan, Sui Kun. Context-based Multi-stage Offline Handwritten Mathematical Symbol Recognition using Deep Learning.

Degree: MS, Computer Science, 2019, San Jose State University

  We propose a multi-stage machine learning (ML) architecture to improve the accuracy of offline handwritten mathematical symbol recognition. In the first stage, we train… (more)

Subjects/Keywords: Competition on Recognition of Online Handwritten Mathematical Expressions (CROHME). Context-based Offline Handwritten Mathematical Recognition. Convolutional Neural Network (CNN). HAndwritten SYmbols (HASYv2). Machine Learning (ML). Multi-Column Deep Neural Network (MCDNN).; Artificial Intelligence and Robotics

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APA (6th Edition):

Guan, S. K. (2019). Context-based Multi-stage Offline Handwritten Mathematical Symbol Recognition using Deep Learning. (Masters Thesis). San Jose State University. Retrieved from https://doi.org/10.31979/etd.zbq2-vv3n ; https://scholarworks.sjsu.edu/etd_projects/732

Chicago Manual of Style (16th Edition):

Guan, Sui Kun. “Context-based Multi-stage Offline Handwritten Mathematical Symbol Recognition using Deep Learning.” 2019. Masters Thesis, San Jose State University. Accessed April 03, 2020. https://doi.org/10.31979/etd.zbq2-vv3n ; https://scholarworks.sjsu.edu/etd_projects/732.

MLA Handbook (7th Edition):

Guan, Sui Kun. “Context-based Multi-stage Offline Handwritten Mathematical Symbol Recognition using Deep Learning.” 2019. Web. 03 Apr 2020.

Vancouver:

Guan SK. Context-based Multi-stage Offline Handwritten Mathematical Symbol Recognition using Deep Learning. [Internet] [Masters thesis]. San Jose State University; 2019. [cited 2020 Apr 03]. Available from: https://doi.org/10.31979/etd.zbq2-vv3n ; https://scholarworks.sjsu.edu/etd_projects/732.

Council of Science Editors:

Guan SK. Context-based Multi-stage Offline Handwritten Mathematical Symbol Recognition using Deep Learning. [Masters Thesis]. San Jose State University; 2019. Available from: https://doi.org/10.31979/etd.zbq2-vv3n ; https://scholarworks.sjsu.edu/etd_projects/732


San Jose State University

25. Ramanathan, Muthaiah. AN ENSEMBLE MODEL FOR CLICK THROUGH RATE PREDICTION.

Degree: MS, Computer Science, 2019, San Jose State University

  Internet has become the most prominent and accessible way to spread the news about an event or to pitch, advertise and sell a product,… (more)

Subjects/Keywords: Click-through rrate prediction; online advertising; Artificial Intelligence and Robotics; Databases and Information Systems

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APA (6th Edition):

Ramanathan, M. (2019). AN ENSEMBLE MODEL FOR CLICK THROUGH RATE PREDICTION. (Masters Thesis). San Jose State University. Retrieved from https://doi.org/10.31979/etd.mj3u-42a6 ; https://scholarworks.sjsu.edu/etd_projects/697

Chicago Manual of Style (16th Edition):

Ramanathan, Muthaiah. “AN ENSEMBLE MODEL FOR CLICK THROUGH RATE PREDICTION.” 2019. Masters Thesis, San Jose State University. Accessed April 03, 2020. https://doi.org/10.31979/etd.mj3u-42a6 ; https://scholarworks.sjsu.edu/etd_projects/697.

MLA Handbook (7th Edition):

Ramanathan, Muthaiah. “AN ENSEMBLE MODEL FOR CLICK THROUGH RATE PREDICTION.” 2019. Web. 03 Apr 2020.

Vancouver:

Ramanathan M. AN ENSEMBLE MODEL FOR CLICK THROUGH RATE PREDICTION. [Internet] [Masters thesis]. San Jose State University; 2019. [cited 2020 Apr 03]. Available from: https://doi.org/10.31979/etd.mj3u-42a6 ; https://scholarworks.sjsu.edu/etd_projects/697.

Council of Science Editors:

Ramanathan M. AN ENSEMBLE MODEL FOR CLICK THROUGH RATE PREDICTION. [Masters Thesis]. San Jose State University; 2019. Available from: https://doi.org/10.31979/etd.mj3u-42a6 ; https://scholarworks.sjsu.edu/etd_projects/697


San Jose State University

26. Deshmukh, Kunal Rajan. Image Compression Using Neural Networks.

Degree: MS, Computer Science, 2019, San Jose State University

  Image compression is a well-studied field of Computer Vision. Recently, many neural network based architectures have been proposed for image compression as well as… (more)

Subjects/Keywords: Convolutional Neural Networks; Generative Adversarial Networks; Artificial Intelligence and Robotics

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APA (6th Edition):

Deshmukh, K. R. (2019). Image Compression Using Neural Networks. (Masters Thesis). San Jose State University. Retrieved from https://doi.org/10.31979/etd.h8mt-65ct ; https://scholarworks.sjsu.edu/etd_projects/666

Chicago Manual of Style (16th Edition):

Deshmukh, Kunal Rajan. “Image Compression Using Neural Networks.” 2019. Masters Thesis, San Jose State University. Accessed April 03, 2020. https://doi.org/10.31979/etd.h8mt-65ct ; https://scholarworks.sjsu.edu/etd_projects/666.

MLA Handbook (7th Edition):

Deshmukh, Kunal Rajan. “Image Compression Using Neural Networks.” 2019. Web. 03 Apr 2020.

Vancouver:

Deshmukh KR. Image Compression Using Neural Networks. [Internet] [Masters thesis]. San Jose State University; 2019. [cited 2020 Apr 03]. Available from: https://doi.org/10.31979/etd.h8mt-65ct ; https://scholarworks.sjsu.edu/etd_projects/666.

Council of Science Editors:

Deshmukh KR. Image Compression Using Neural Networks. [Masters Thesis]. San Jose State University; 2019. Available from: https://doi.org/10.31979/etd.h8mt-65ct ; https://scholarworks.sjsu.edu/etd_projects/666


San Jose State University

27. Shah, Abhishek. Approximate Disassembly using Dynamic Programming.

Degree: MS, Computer Science, 2010, San Jose State University

 Most commercial anti-virus software uses signature based techniques to detect whether a file is infected by a virus or not. However, signature based detection systems… (more)

Subjects/Keywords: anit-virus dynamic programming disassembly; Other Computer Sciences

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APA (6th Edition):

Shah, A. (2010). Approximate Disassembly using Dynamic Programming. (Masters Thesis). San Jose State University. Retrieved from https://doi.org/10.31979/etd.8m5n-rxtz ; https://scholarworks.sjsu.edu/etd_projects/8

Chicago Manual of Style (16th Edition):

Shah, Abhishek. “Approximate Disassembly using Dynamic Programming.” 2010. Masters Thesis, San Jose State University. Accessed April 03, 2020. https://doi.org/10.31979/etd.8m5n-rxtz ; https://scholarworks.sjsu.edu/etd_projects/8.

MLA Handbook (7th Edition):

Shah, Abhishek. “Approximate Disassembly using Dynamic Programming.” 2010. Web. 03 Apr 2020.

Vancouver:

Shah A. Approximate Disassembly using Dynamic Programming. [Internet] [Masters thesis]. San Jose State University; 2010. [cited 2020 Apr 03]. Available from: https://doi.org/10.31979/etd.8m5n-rxtz ; https://scholarworks.sjsu.edu/etd_projects/8.

Council of Science Editors:

Shah A. Approximate Disassembly using Dynamic Programming. [Masters Thesis]. San Jose State University; 2010. Available from: https://doi.org/10.31979/etd.8m5n-rxtz ; https://scholarworks.sjsu.edu/etd_projects/8


San Jose State University

28. Yang, Fan. Automatic Execution Path Finding Tool.

Degree: MS, Computer Science, 2010, San Jose State University

 Today, there are many hackers trying to break software using reverse engineering tech- niques. To better protect software, we need to understand reverse engineering methods.… (more)

Subjects/Keywords: reverse engineering software security; Other Computer Sciences; Programming Languages and Compilers

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APA (6th Edition):

Yang, F. (2010). Automatic Execution Path Finding Tool. (Masters Thesis). San Jose State University. Retrieved from https://doi.org/10.31979/etd.92qu-pfft ; https://scholarworks.sjsu.edu/etd_projects/13

Chicago Manual of Style (16th Edition):

Yang, Fan. “Automatic Execution Path Finding Tool.” 2010. Masters Thesis, San Jose State University. Accessed April 03, 2020. https://doi.org/10.31979/etd.92qu-pfft ; https://scholarworks.sjsu.edu/etd_projects/13.

MLA Handbook (7th Edition):

Yang, Fan. “Automatic Execution Path Finding Tool.” 2010. Web. 03 Apr 2020.

Vancouver:

Yang F. Automatic Execution Path Finding Tool. [Internet] [Masters thesis]. San Jose State University; 2010. [cited 2020 Apr 03]. Available from: https://doi.org/10.31979/etd.92qu-pfft ; https://scholarworks.sjsu.edu/etd_projects/13.

Council of Science Editors:

Yang F. Automatic Execution Path Finding Tool. [Masters Thesis]. San Jose State University; 2010. Available from: https://doi.org/10.31979/etd.92qu-pfft ; https://scholarworks.sjsu.edu/etd_projects/13


San Jose State University

29. Joshi, Arunesh. EVALUATION OF CLASSICAL INTER-PROCESS COMMUNICATION PROBLEMS IN PARALLEL PROGRAMMING LANGUAGES.

Degree: MS, Computer Science, 2011, San Jose State University

  It is generally believed for the past several years that parallel programming is the future of computing technology due to its incredible speed and… (more)

Subjects/Keywords: Parallel Programming Synchronization; OS and Networks; Systems Architecture

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Joshi, A. (2011). EVALUATION OF CLASSICAL INTER-PROCESS COMMUNICATION PROBLEMS IN PARALLEL PROGRAMMING LANGUAGES. (Masters Thesis). San Jose State University. Retrieved from https://doi.org/10.31979/etd.btq9-m69c ; https://scholarworks.sjsu.edu/etd_projects/172

Chicago Manual of Style (16th Edition):

Joshi, Arunesh. “EVALUATION OF CLASSICAL INTER-PROCESS COMMUNICATION PROBLEMS IN PARALLEL PROGRAMMING LANGUAGES.” 2011. Masters Thesis, San Jose State University. Accessed April 03, 2020. https://doi.org/10.31979/etd.btq9-m69c ; https://scholarworks.sjsu.edu/etd_projects/172.

MLA Handbook (7th Edition):

Joshi, Arunesh. “EVALUATION OF CLASSICAL INTER-PROCESS COMMUNICATION PROBLEMS IN PARALLEL PROGRAMMING LANGUAGES.” 2011. Web. 03 Apr 2020.

Vancouver:

Joshi A. EVALUATION OF CLASSICAL INTER-PROCESS COMMUNICATION PROBLEMS IN PARALLEL PROGRAMMING LANGUAGES. [Internet] [Masters thesis]. San Jose State University; 2011. [cited 2020 Apr 03]. Available from: https://doi.org/10.31979/etd.btq9-m69c ; https://scholarworks.sjsu.edu/etd_projects/172.

Council of Science Editors:

Joshi A. EVALUATION OF CLASSICAL INTER-PROCESS COMMUNICATION PROBLEMS IN PARALLEL PROGRAMMING LANGUAGES. [Masters Thesis]. San Jose State University; 2011. Available from: https://doi.org/10.31979/etd.btq9-m69c ; https://scholarworks.sjsu.edu/etd_projects/172


San Jose State University

30. Kathiravan, Manodivya. WEB - BASED OFFICE MARKET.

Degree: MS, Computer Science, 2017, San Jose State University

  People who work in an office often have different pools of resources that they want to exchange. They want to trade their resources/work(seller) with… (more)

Subjects/Keywords: Multi-way Web Based Barter Exchange; auction systems; Other Computer Sciences; Software Engineering

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Kathiravan, M. (2017). WEB - BASED OFFICE MARKET. (Masters Thesis). San Jose State University. Retrieved from https://doi.org/10.31979/etd.ejxr-m56a ; https://scholarworks.sjsu.edu/etd_projects/534

Chicago Manual of Style (16th Edition):

Kathiravan, Manodivya. “WEB - BASED OFFICE MARKET.” 2017. Masters Thesis, San Jose State University. Accessed April 03, 2020. https://doi.org/10.31979/etd.ejxr-m56a ; https://scholarworks.sjsu.edu/etd_projects/534.

MLA Handbook (7th Edition):

Kathiravan, Manodivya. “WEB - BASED OFFICE MARKET.” 2017. Web. 03 Apr 2020.

Vancouver:

Kathiravan M. WEB - BASED OFFICE MARKET. [Internet] [Masters thesis]. San Jose State University; 2017. [cited 2020 Apr 03]. Available from: https://doi.org/10.31979/etd.ejxr-m56a ; https://scholarworks.sjsu.edu/etd_projects/534.

Council of Science Editors:

Kathiravan M. WEB - BASED OFFICE MARKET. [Masters Thesis]. San Jose State University; 2017. Available from: https://doi.org/10.31979/etd.ejxr-m56a ; https://scholarworks.sjsu.edu/etd_projects/534

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