TU1.M3.1
Few-Shot Semantic Change Detection in Satellite Imagery Using Neural and Transformer Models
Madeline Anderson, Kerri Cahoy, Massachusetts Institute of Technology, United States
Session:
TU1.M3: Deep Learning for Semantic Segmentation & Change Detection in Remote Sensing II Oral
Track:
AI and Big Data
Location:
Room M3
Presentation Time:
Tuesday, 5 August, 08:00 - 08:15
Presentation
Discussion
Resources
No resources available.
Session TU1.M3
TU1.M3.1: Few-Shot Semantic Change Detection in Satellite Imagery Using Neural and Transformer Models
Madeline Anderson, Kerri Cahoy, Massachusetts Institute of Technology, United States
TU1.M3.2: DOMAIN ADAPTIVE TEMPORAL CONVOLUTIONAL NEURAL NETWORKS FOR CONTINUOUS CHANGE DETECTION IN THE ALBANY THICKET BIOME
Craig Mahlasi, University of Cape Town, South Africa; Glenn Moncrieff, The Nature Conservancy, South Africa; Vernon Visser, Jasper Slingsby, University of Cape Town, South Africa
TU1.M3.3: EHRNET FOR BUILDING EXTRACTION AND CONTOUR OPTIMIZATION
Buyu Su, Piyuan Yi, Beijing Research Institute of Uranium Geology, China; Wenhuan Wu, Beijing Research Institute of Uranium Geology and Beijing Normal University, China; Haowei Mu, Nanjing University, China
TU1.M3.4: ANOMALYCM: MONITORING ANOMALY CHANGES ON LAND SURFACE WITH TIME-SERIES HIGH-SPATIAL RESOLUTION SATELLITE IMAGERY
Jingtao Li, Qian Zhu, Xinyu Wang, Yanfei Zhong, Wuhan university, China
TU1.M3.5: MULTIMODAL SEMANTIC CHANGE DETECTION WITH BACKGROUND HEIGHT AWARENESS
Biyuan Liu, Sijie Luo, Jinpeng He, Huaixin Chen, University of Electronic Science and Technology of China, China
Resources
No resources available.