WE2.R2.3

RADARGRAMS AS SEQUENCES: A METHOD FOR THE SEMANTIC SEGMENTATION OF RADAR SOUNDER DATA

Jordy Dal Corso, Lorenzo Bruzzone, Università di Trento, Italy
Session:
WE2.R2: Weak Supervision For Segmentation Oral
Track:
Data Analysis
Location:
Mitropoulos
Presentation Time:
Wed, 10 Jul, 12:08 - 12:22
Session Co-Chairs:
Devis Tuia, EPFL and Shutao Li, Hunan University
Presentation
Discussion
Resources
No resources available.
Session WE2.R2
WE2.R2.1: Learning from Unlabelled Data with Transformers: Domain Adaptation for Semantic Segmentation of High Resolution Aerial Images
Nikolaos Dionelis, European Space Agency (ESA), Italy; Francesco Pro, Luca Maiano, Irene Amerini, Sapienza University of Rome, Italy; Bertrand Le Saux, European Space Agency (ESA), Italy
WE2.R2.2: KNOWLEDGE DISTILLATION FOR ROAD DETECTION BASED ON CROSS-MODEL SEMI-SUPERVISED LEARNING
Wanli Ma, Oktay Karakus, Paul L. Rosin, Cardiff University, United Kingdom
WE2.R2.3: RADARGRAMS AS SEQUENCES: A METHOD FOR THE SEMANTIC SEGMENTATION OF RADAR SOUNDER DATA
Jordy Dal Corso, Lorenzo Bruzzone, Università di Trento, Italy
WE2.R2.4: DISENTANGLING SEMI-SUPERVISED SEMANTIC SEGMENTATION OF REMOTE SENSING IMAGES
Wei Huang, Yilei Shi, Zhitong Xiong, Xiaoxiang Zhu, Technical University of Munich, Germany
WE2.R2.5: SPARSE POINT ANNOTATIONS AND ITERATIVE ACTIVE LEARNING FOR VEHICLE DETECTION
Osmar Luiz Carvalho, Osmar Abílio de Carvalho Junior, Anesmar Albuquerque, Daniel Silva, University of Brasília, Brazil
WE2.R2.6: ALLEVIATING SEMANTIC UNCERTAINTY IN CAMS FOR WEAKLY-SUPERVISED LAND-COVER CLASSIFICATION
Qiyuan Ma, Linxi Huan, Mingyue Dong, Xianwei Zheng, Wuhan University, China; Linwei Yue, China University of Geosciences, China
WE2.R2.7: REGION-AWARE CONTRASTIVE LEARNING FOR SEMI-SUPERVISED SEMANTIC SEGMENTATION OF REMOTE SENSING IMAGES
Yuan Luo, Bin Sun, Shutao Li, Hunan University, China
Resources
No resources available.