TH4.P11.1
CEASeg: Cross-modal Efficient Attention Semantic Segmentation Method for Remote Sensing Images
Huayu Zhang, Yufeng Wang, Zehao Zhang, Dacheng Qi, Wenrui Ding, Beihang University, China
Session:
TH4.P11: Multi-source Semantic Segmentation Oral
Track:
Data Analysis
Location:
Room P11
Presentation Time:
Thursday, 7 August, 15:45 - 16:00
Presentation
Discussion
Resources
No resources available.
Session TH4.P11
TH4.P11.1: CEASeg: Cross-modal Efficient Attention Semantic Segmentation Method for Remote Sensing Images
Huayu Zhang, Yufeng Wang, Zehao Zhang, Dacheng Qi, Wenrui Ding, Beihang University, China
TH4.P11.2: ON WHAT DEPENDS THE ROBUSTNESS OF MULTI-SOURCE MODELS TO MISSING DATA IN EARTH OBSERVATION?
Francisco Mena, University of Kaiserslautern-Landau, Germany; Diego Arenas, German Research Center for Artificial Intelligence (DFKI), Germany; Miro Miranda, University of Kaiserslautern-Landau, Germany; Andreas Dengel, German Research Center for Artificial Intelligence (DFKI), Germany
TH4.P11.3: Multisource Noise-Reduced Diffusion Feature Fusion for Hyperspectral and SAR Image Classification
Hao Liu, Yongjie Zheng, Lorenzo Bruzzone, University of Trento, Italy
TH4.P11.4: Multi-Frequency Graph Convolutional Network With Cross-Modality Mutual Enhancement for Multisource Remote Sensing Data Classification
Jin-yu Yang, Heng-chao Li, Jing-hua Yang, Lei Pan, Southwest Jiaotong University, China; Qian Du, Mississippi State Univerwsity, United States; Antonio Plaza, University of Extremadura, Spain
TH4.P11.5: VULNERABILITIES OF MULTIMODAL FUSION MODELS IN REMOTE SENSING: ANALYZING THE IMPACT OF ADVERSARIAL ATTACKS ON SPATIAL DATA CONTENT
Chaman Banolia, Tata Consultancy Services, India; Biplab Banerjee, IIT Bombay, India; Shailesh Deshpande, Tata Consultancy Services, India
Resources
No resources available.