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1.
Firmware and classification algorithm development for vehicle classification
by Ravindra, Dilip, M.S.  California State University, Long Beach. 2015: 37 pages; 1603749.
2.
Automatic detection and classification of prosodic events
by Rosenberg, Andrew, Ph.D.  Columbia University. 2009: 381 pages; 3393597.
4.
Detection of Canine Bone Cancer Using Artificial Neural Networks
by Gorre, Naveena, M.S.  Southern Illinois University at Edwardsville. 2020: 70 pages; 27957796.
5.
A new distributed framework for cyber attack detection and classification
by Gutta, Sandeep, M.S.  Oklahoma State University. 2011: 86 pages; 1506488.
6.
Levee slide detection using synthetic aperture radar magnitude and phase
by Marapareddy, Ramakalavathi, Ph.D.  Mississippi State University. 2015: 196 pages; 3737165.
8.
A Software Framework for the Detection and Classification of Biological Targets in Bio-Nano Sensing
by Hafeez, Abdul, Ph.D.  Virginia Polytechnic Institute and State University. 2014: 112 pages; 10595350.
9.
A structure based technique for spam detection and email classification
by Desai, Varun, M.S.  California State University, Long Beach. 2016: 56 pages; 10017844.
10.
A computer vision approach to classification of circulating tumor cells
by Hopkins, David, M.S.  Colorado State University. 2013: 93 pages; 1539638.
11.
Thermographic Image Analysis as a Pre-Screening Tool for the Detection of Canine Bone Cancer
by Subedi, Samrat, M.S.  Southern Illinois University at Edwardsville. 2014: 131 pages; 1583211.
13.
Distributed Intelligence for Online Situational Awareness and Resilience in Power Grids
by Wang, Shiyuan, Ph.D.  The George Washington University. 2020: 171 pages; 28090236.
16.
Background and Occlusion Defenses Against Adversarial Examples and Adversarial Patches
by McCoyd, Michael J., Ph.D.  University of California, Berkeley. 2020: 75 pages; 28090541.
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19.
Graph-based Event Correlation for Network Security Defense
by Neise, Patrick, D.Engr.  The George Washington University. 2018: 96 pages; 10785425.
20.
Vehicle classification method for use with rapidly emplaced mobile bridges: A sensitivity study
by Rovira, Ricardo E. Basora, M.S.C.E.  Purdue University. 2015: 110 pages; 10044106.
21.
Machine-Learning Methods for Credit Card Fraud Detection
by Woolston, Sarah E., M.S.  California State University, Long Beach. 2017: 100 pages; 10602012.
23.
Machine Learning Methods for 3D Object Classification and Segmentation
by Le, Truc Duc, Ph.D.  University of Missouri - Columbia. 2018: 158 pages; 13877153.
24.
In-Node Vehicle Classification and Identification
by Bavkar, Indraneel N., M.S.  California State University, Long Beach. 2017: 50 pages; 10639676.
25.
Deep Learning for Information Extraction
by Nguyen, Thien Huu, Ph.D.  New York University. 2018: 246 pages; 10260911.
27.
Various considerations on performance measures for a classification of ordinal data
by Nyongesa, Denis Barasa, M.S.  California State University, Long Beach. 2016: 111 pages; 10133995.
28.
Precise Vehicle Classification Using a Quarter Sized Sensing System
by Patel, Kuntal G., M.S.  California State University, Long Beach. 2017: 82 pages; 10263671.
30.
Image classification using invariant local features and contextual information
by Bharath, Ramesh, Ph.D.  National University of Singapore (Singapore). 2015: 178 pages; 10006074.
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