TU1.R13.2
A SELF-CONSISTENT APPROACH TO HIERARCHICAL REMOTE SENSING IMAGE CLASSIFICATION
Giulio Weikmann, Gianmarco Perantoni, Lorenzo Bruzzone, University of Trento, Italy
Session:
TU1.R13: Deep Learning for Classification Oral
Track:
Theory and Techniques
Location:
Georgetown West
Presentation Time:
Tuesday, 11 August, 08:45 - 09:00
Session Co-Chairs:
Lorenzo Bruzzone, University of Trento and Gabriele Cavallaro, University of Iceland
Presentation
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Session TU1.R13
TU1.R13.1: Deep Linear Discriminant Analysis with Discriminative NLL Loss for Remote Sensing Tasks
Arman Bolatov, National Center of Space Research and Technology, United Arab Emirates; Rustem Kaliyev, Institute of Mathematics and Mathematical Modeling, Kazakhstan; Amantay Nurlanuly, JSC National Center of Space Research and Technology, Kazakhstan; Zhenisbek Assylbekov, National Center of Space Research and Technology, Kazakhstan
TU1.R13.2: A SELF-CONSISTENT APPROACH TO HIERARCHICAL REMOTE SENSING IMAGE CLASSIFICATION
Giulio Weikmann, Gianmarco Perantoni, Lorenzo Bruzzone, University of Trento, Italy
TU1.R13.3: A MODALITY-AWARE FUSION NETWORK FOR LAND COVER CLASSIFICATION
Huiting Li, Jingru Zhu, Tianyi Xu, Jie Chen, Central South University, China
TU1.R13.4: WE-MAMBA: A MAMBA-ENHANCED U-NET FOR WEAK EARTHQUAKE DETECTION AND PHASE PICKING
Chenglin Jiang, Tong Shen, Yadi Wang, Fei Han, Yiming Han, Southwest University of Science and Technology, China; Jinfu Li, School of Optics and Photonics, Beijing Institute of Technology, China
TU1.R13.5: IMPROVED KNOWLEDGE DISTILLATION FOR LAND-USE IMAGE CLASSIFICATION
Arundhuti Sur, Abhiroop Chatterjee, Susmita Ghosh, Jadavpur University, India; Emmett Ientilucci, Rochester Institute of Technology, United States
Resources
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