CDCEO 2022

Complex Data Challenges in Earth Observation 2022

Table of Contents

• Preface
  i-iv
  

Regular Track

• A Center-Masked Convolutional Transformer for Hyperspectral Image Classification 1-6
  Yifan Wang, Shuguo Jiang, Meng Xu, Shuyu Zhang, Sen Jia
• A Deep Feature Retrieved Network for Bitemporal Remote Sensing Image Change Detection 7-13
  Shizhen Chang, Michael Kopp, Pedram Ghamisi
• "Disaster Detection from SAR Images with Different Off-Nadir Angles Using Unsupervised Image Translation 14-20
  Jian Song, Bruno Adriano, Naoto Yokoya
• Knowledge-Aware Cross-Modal Text-Image Retrieval for Remote Sensing Images 21-26
  Li Mi, Siran Li, Christel Chappuis, Devis Tuia
• Mapping Slums with Deep Learning Feature Extraction 27-32
  Agatha Mattos, Michela Bertolotto, Gavin McArdle
• METER-ML: A Multi-Sensor Earth Observation Benchmark for Automated Methane Source Mapping 33-43
  Bryan Zhu, Nicholas Lui, Jeremy Irvin, Jimmy Le, Sahil Tadwalkar, Chenghao Wang, Zutao Ouyang, Frankie Y. Liu, Andrew Y. Ng, Robert B. Jackson
• Model-Centric vs Data-Centric Deep Learning Approaches for Landslide Detection 44-49
  Hejar Shahabi, Omid Ghorbanzadeh
• Multimodal Crop Type Classification Fusing Multi-Spectral Satellite Time Series with Farmers Crop Rotations and Local Crop Distribution 50-57
  Valentin Barriere, Martin Claverie
• Predicting Flood Inundation Depth Based-on Machine Learning and Numerical Simulation 58-64
  Bruno Adriano, Naoto Yokoya, Satoru Oishi
• Radar-Based Volumetric Precipitation Nowcasting: A 3D Convolutional Neural Network with U-Net Architecture 65-72
  Peter Pavlík, Viera Rozinajová, Anna Bou Ezzeddine
• Task-Guided Denoising Network for Adversarial Defense of Remote Sensing Scene Classification 73-78
  Yonghao Xu, Weikang Yu, Pedram Ghamisi
• Weak-Supervision Based on Label Proportions for Earth Observation Applications from Optical and Hyperspectral Imagery 79-85
  Laura E. Cué La Rosa, Dário A. Borges Oliveira, Sam Thiele, Pedram Ghamisi, Richard Gloaguen

Landslide4Sense Track

• The Landslide4Sense Competition 2022 86-87
  Pedram Ghamisi, Omid Ghorbanzadeh, Yonghao Xu, Pedro Herruzo, David Kreil, Michael Kopp, Sepp Hochreiter
• Progressive Label Refinement-Based Distribution Adaptation Framework for Landslide Detection 88-91
  Hengwei Zhao, Junjue Wang, Yang Pan, Ailong Ma, Xinyu Wang, Yanfei Zhong
• SwinLS: Adapting Swin Transformer to Landslide Detection 92-96
  Dong Zhao, Qi Zang, Zining Wang, Dou Quan, Shuang Wang
• On the Generalization of the Semantic Segmentation Model for Landslide Detection 97-101
  Fahong Zhang, Yilei Shi, Qingsong Xu, Zhitong Xiong, Wei Yao, Xiao Xiang Zhu
• Multispectral U-Net: A Semantic Segmentation Model Using Multispectral Bands Fusion Mechanism for Landslide Detection 102-105
  Lin Bai, Weile Li, Qiang Xu, Weihang Peng, Kai Chen, Zhenzhen Duan, Huiyan Lu