MO1.R2: Scene Classification
Mon, 17 Jul, 13:00 - 14:15 Pacific Time (UTC -7)
Location: Room 2
Session Type: Oral
Session Chair: Begüm Demir, Technische Universität Berlin
Track: Data Analysis
Mon, 17 Jul, 13:00 - 13:12 Pacific Time (UTC -7)

MO1.R2.1: A MULTI-SCALE DEEP FEATURE LEARNING AND SEMANTIC ENHANCEMENT APPROACH FOR REMOTE SENSING SCENE CLASSIFICATION
Hengyi Huang, Wenzhen Wang, Liang Xiao, Nanjing University of Science and Technology, China; Wenzhi Liao, Flanders Make and Ghent University, Belgium
Mon, 17 Jul, 13:12 - 13:24 Pacific Time (UTC -7)

MO1.R2.2: REMOTE SENSING IMAGE SCENE CLASSIFICATION BASED ON CONTRASTIVE CAPSULE NETWORK
Liang Hao, ZhiWen Liu, University of Electronic Science and Technology of China,, China
Mon, 17 Jul, 13:24 - 13:36 Pacific Time (UTC -7)

MO1.R2.3: C-NOISYSTUDENT: CURRICULUM LEARNING WITH NOISY STUDENT IMPROVES REMOTE SENSING SCENE CLASSIFICATION
Xinglin Gao, Hao Wang, Sheng Chang, Yi Xiao, Shuxing Huang, Xianchuan Yu, Beijing Normal University, China; Haihua Xing, Hainan Normal University, China
Mon, 17 Jul, 13:36 - 13:48 Pacific Time (UTC -7)

MO1.R2.4: FROM COARSE TO FINE: KNOWLEDGE DISTILLATION FOR REMOTE SENSING SCENE CLASSIFICATION
JINSHENG JI, Nanyang Technological University, China; XIAOMING XI, Shandong Jianzhu University, China; XIANKAI LU, Shandong University, China; YIYOU GUO, HUAN XIE, Tongji University, China
Mon, 17 Jul, 13:48 - 14:00 Pacific Time (UTC -7)

MO1.R2.5: INCREMENTAL LEARNING METHODS BASED ON KNOWLEDGE REPRODUCTION
Bin Li, Yijie Deng, Jizhen Ma, Zongjie Cao, University of Electronic Science and Technology of China, China
Mon, 17 Jul, 14:00 - 14:15 Pacific Time (UTC -7)

MO1.R2.D: Discussion