TA.L306: Adversarial Learning for Image Processing
Tue, 10 Oct, 11:00 - 12:30 Malaysia Time (UTC +8)
Location: Room 306
Session Type: Lecture
Session Chair: William Puech, Université de Montpellier, FRANCE
Track: Applications of Machine Learning
Click the to view the manuscript on IEEE Xplore Open Preview
Tue, 10 Oct, 11:00 - 11:18 Malaysia Time (UTC +8)
 

TA.L306.1: EXPLORING THE CONNECTION BETWEEN NEURON COVERAGE AND ADVERSARIAL ROBUSTNESS IN DNN CLASSIFIERS
William Piat, Safran Tech / Univ. Caen, France; Jalal Fadili, École nationale supérieure d'ingénieurs de Caen - ENSICAEN, France; Frédéric Jurie, University of Caen Normandie, France
Tue, 10 Oct, 11:18 - 11:36 Malaysia Time (UTC +8)
 

TA.L306.2: ADVERSARIAL EXAMPLE DETECTION BAYESIAN GAME
Hui Zeng, Southwest university of science and technology, China; Biwei Chen, Beijing Normal University, China; Kang Deng, Anjie Peng, Southwest University of Science and Technology, China
Tue, 10 Oct, 11:36 - 11:54 Malaysia Time (UTC +8)
 

TA.L306.3: DATA GENERATION WITH STRUCTURE ENFORCING ADVERSARIAL LEARNING
Indu Solomon, Uttam Kumar, International Institute of Information Technology Bangalore, India; Senthilnath Jayavelu, Institute for Infocomm Research, Agency for Science Technology and Research (A*STAR), Singapore
Tue, 10 Oct, 11:54 - 12:12 Malaysia Time (UTC +8)
 

TA.L306.4: A PENALIZED MODIFIED HUBER REGULARIZATION TO IMPROVE ADVERSARIAL ROBUSTNESS
Modeste Atsague, Ashutosh Nirala, Olukorede Fakorede, Jin Tian, Iowa State University, United States of America
Tue, 10 Oct, 12:12 - 12:30 Malaysia Time (UTC +8)

TA.L306.5: Purifying Adversarial Images using Adversarial Autoencoders with Conditional Normalizing Flows
Yi Ji, University of Tokyo; Trung-Nghia Le, National Institute of Informatics; Huy Nguyen, Graduate University for Advanced Studies; Isao Echizen, National Institute of Informatics