TUP.P9: Deep Learning for Change Detection
Tue, 18 Jul, 14:15 - 15:45 Pacific Time (UTC -7)
Location: Poster Area 9
Session Type: Poster
Track: Data Analysis

TUP.P9.1: A SIAMESE DIFFERENTIAL NETWORK WITH GLOBAL CONTEXT ENHANCEMENT FOR BITEMPORAL REMOTE SENSING IMAGES CHANGE DETECTION

Wen Wang, Zhejiang Lab, China; Bingqing Hong, Beijing Huahang Radio Measurement Institute, China

TUP.P9.2: SRNET: SIAMESE RESIDUAL NETWORK FOR REMOTE SENSING CHANGE DETECTION

Yue Yang, Tao Chen, School of Geophysics and Geomatics, China University of Geosciences, Wuhan 430074, China, China; Jun Li, China University of Geosciences, China University of Geosciences, Wuhan 430074, China, China

TUP.P9.3: A SIAMESE NETWORK FOR SEMANTIC CHANGE DETECTION BASED ON MULTISCALE CONTEXT FUSION

Chang Li, Rongfang Wang, Jia-Wei Chen, Yi Niu, Changzhe Jiao, Xidian University, China; Chunlei Huo, Chinese Academy of Sciences, China

TUP.P9.4: HYBRID TRANSFORMER NETWORK FOR CHANGE DETECTION UNDER SELF-SUPERVISED PRETRAINING

Yongjing Cui, Yin Zhuang, Shan Dong, Xinyi Zhang, He Chen, Liang Chen, Beijing Key Laboratory of Embedded Real-time Information Processing Technology, Beijing Institute of Technology, China; Peng Gao, Shanghai AI Laboratory, China

TUP.P9.5: «LOW SUPERVISION» DEEP CLUSTER CHANGE DETECTION (CDCLUSTER) ON REMOTE SENSING RGB DATA: TOWARDS THE UNSUPERVISING CLUSTERING FRAMEWORK

Guglielmo Fernandez Garcia, Thomas Corpetti, Université Rennes 2, France; Iris de Gelis, Magelium, France; Sébastien Lefèvre, Université Bretagne Sud, France; Arnaud Le Bris, Institut Géographique National, France

TUP.P9.7: SWIN RESNET: SWIN TRANSFORMERS FOR CHANGE DETECTION IN REMOTE SENSING IMAGES

Xu Liu, Yu Liu, Licheng Jiao, Lingling Li, Fang Liu, Dan Zhang, xidian university, China