WE2.M3.4
PirNet: A Mutimodal Remote Sensing Change Detection Network
Zichen Yang, Zichen Yang, Institute of Automation, Chinese Academy of Sciences, China
Session:
WE2.M3: Deep Learning Approaches for Object Detection and Recognition in Remote Sensing III Oral
Track:
AI and Big Data
Location:
Mezzanine: Room M3
Presentation Time:
Wednesday, 6 August, 11:15 - 11:30
Session Co-Chairs:
Nick LaHaye, SIG - Spatial Informatics Group and Chetan Mahajan, IIT Bombay
Session WE2.M3
WE2.M3.1: AERIAL ORIENTED OBJECT DETECTION WITH RASTERIZED POLYGON-BASED LEARNING
Yuyuan Zhuang, Junpeng Zhang, Jie Feng, Xidian University, China; Jue Zhang, Griffith University, Australia
WE2.M3.2: EARTHQUAKE FALSE ALARM DETECTION MODEL AUGMENTED WITH SPARSE PROFILE ANALYSIS
Jungeun Yoon, Aekyeung Moon, Electronics and Telecommunications Research Institute, Korea (South); Seung Woo Son, University of Massachusetts Lowell, United States
WE2.M3.3: Data Augmentation Strategy for Ship Detection in Few-shot Remote Sensing Images
Danshu Zhou, Yushan Xiong, Jian Liu, Nanjian Wu, Runjiang Dou, Liyuan Liu, Institute of Semiconductors, Chinese Academy of Sciences, China
WE2.M3.4: PirNet: A Mutimodal Remote Sensing Change Detection Network
Zichen Yang, Zichen Yang, Institute of Automation, Chinese Academy of Sciences, China
WE2.M3.5: SEMANTIC DISTANCE MODELING FOR MULTI-GRANULARITY CLASSES IN HIERARCHICAL SHIP CLASSIFICATION
Jingzhou Chen, Junjie Huang, Fengchao Xiong, Liang Xiao, Nanjing University of Science and Technology, China; Yuntao Qian, Zhejiang University, China
Resources