TH2.R2.1: AUTOMATED DEEP LEARNING-BASED POINT CLOUD CLASSIFICATION ON USGS 3DEP LIDAR DATA USING A TRANSFORMER
Jung kuan Liu, USGS, United States; Rongjun Qin, Shuang Song, The Ohio State University, United States
TH2.R2.2: UNCERTAINTY-INJECTED CROSS-DOMAIN FEW-SHOT SCENE CLASSIFICATION FROM REMOTE SENSING IMAGERY
Can Li, He Chen, Jiahao Li, Yin Zhuang, Liang Chen, Beijing Institute of Technology, China
TH2.R2.3: COMPOSED IMAGE RETRIEVAL FOR REMOTE SENSING
Bill Psomas, Ioannis Kakogeorgiou, National Technical University of Athens, Greece; Nikos Efthymiadis, Giorgos Tolias, Ondřej Chum, Czech Technical University in Prague, Czech Republic; Yannis Avrithis, Institute of Advanced Research in Artificial Intelligence (IARAI), Austria; Konstantinos Karantzalos, National Technical University of Athens, Greece
TH2.R2.4: CONTINUAL LEARNING IN REMOTE SENSING : LEVERAGING FOUNDATION MODELS AND GENERATIVE CLASSIFIERS TO MITIGATE FORGETTING
Marie-Ange Boum, ONERA/CNES, France; Stéphane Herbin, Pierre Fournier, ONERA, France; Pierre Lassalle, CNES, France
TH2.R2.5: A DEEP LEARNING APPROACH FOR IMAGERY MASKING OF SPECTRAL SENSORS
Efrain Padilla-Zepeda, German Aerospace Center (DLR), Germany; Kevin Alonso, Starion Group c/o European Space Agency (ESA), Italy; Raquel De Los Reyes, German Aerospace Center (DLR), Germany; Deni Torres-Roman, Center for Research and Advanced Studies of the National Polytechnic Institute (Cinvestav), Mexico; Avi Putri Pertiwi, German Aerospace Center (DLR), Germany
TH2.R2.7: PDEC-NET: AN IMPROVED SINGLE TREE SEGMENTATION METHOD FOR URBAN MOBILE LASER SCANNING POINT CLOUDS BASED ON PDE-NET
Hao Guan, Ruoxuan Zhang, Tongtong Lu, Qingzhe Lv, Binfu Ge, Fang Huang, University of Electronic Science and Technology of China, China
