WA2.L4.2
LIGHT-WEIGHT SELF-SUPERVISED CONTRASTIVE LEARNING NETWORK FOR SMALL SAMPLE HYPERSPECTRAL IMAGE CLASSIFICATION
Gan Yang, Zhaohui Wang, Hainan University, China
Session:
WA2.L4: Robust Machine Learning Methods for Image & Video Processing - VII Lecture
Track:
Visual Artificial Intelligence
Location:
Capital Suite - 15
Presentation Time:
Wed, 30 Oct, 10:48 - 11:06 Gulf Standard Time (UTC +4)
Session Chair:
Osman Islam, University of British Columbia
Session WA2.L4
WA2.L4.1: A SINGLE GRAPH CONVOLUTION IS ALL YOU NEED: EFFICIENT GRAYSCALE IMAGE CLASSIFICATION
Jacob Fein-Ashley, Sachini Wickramasinghe, Bingyi Zhang, University of Southern California, United States of America; Rajgopal Kannan, DEVCOM Army Research Lab, United States of America; Viktor Prasanna, University of Southern California, United States of America
WA2.L4.2: LIGHT-WEIGHT SELF-SUPERVISED CONTRASTIVE LEARNING NETWORK FOR SMALL SAMPLE HYPERSPECTRAL IMAGE CLASSIFICATION
Gan Yang, Zhaohui Wang, Hainan University, China
WA2.L4.3: MSSPG-AL: FEW-SHOT HYPERSPECTRAL IMAGE CLASSIFICATION WITH ACTIVE LEARNING UPDATED MULTI-SCALE SUPERPIXEL GRAPH FUSION
Long Yu, Sun Yat-sen University, China; Jun Li, China University of Geosciences, China; Li Zhuo, Sun Yat-sen University, China
WA2.L4.4: GRAPHIC - Graph-based Representation for Analyzing People's High-level Interactions in Crowds
Francesco Longobardi, Daniel Riccio, University of Naples Federico II, Italy
WA2.L4.5: Deep optical flow learning with deformable large-kernel Cross-attention
Xuezhi Xiang, Yiming Chen, Denis Ombati, Harbin Engineering University, China; Lei Zhang, Xiantong Zhen, Guangdong University of Petrochemical Technology, China
Contacts