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:
Room M3
Presentation Time:
Wednesday, 6 August, 11:15 - 11:30
Presentation
Discussion
Resources
No resources available.
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
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, Runjiang Dou, Jian Liu, Nanjian Wu, 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: MULTI-TASK LEARNING FOR SMALL OBJECT DETECTION IN HIGH-RESOLUTION SATELLITE IMAGES
Murat Osswald, Louis Niederloehner, Simon Owerien, University of the Bundeswehr Munich, Germany; Michael Mommert, Stuttgart University of Applied Sciences, Germany; Helmut Mayer, University of the Bundeswehr Munich, Germany
Resources
No resources available.