MO4.M3: Deep Learning for Semantic Segmentation & Change Detection in Remote Sensing I
Monday, 4 August, 15:45 - 17:00
Location: Room M3
Session Type: Oral
Session Co-Chairs: Madeline Loui, MIT and Ramesh Nair, Planet
Track: AI and Big Data
Mon, 4 Aug, 15:45 - 16:00

MO4.M3.1: Box-supervised instance segmentation for building rooftop delineation from high spatial resolution remotely sensed imagery
Hongjie He, University of Waterloo, Canada; Nan Chen, Xi’an Aeronautical University, China; Lingfei Ma, University of Finance and Economics, China; Jonathan Li, University of Waterloo, Canada
Mon, 4 Aug, 16:00 - 16:15

MO4.M3.2: MULTI-MODAL DEEP LEARNING APPROACHES TO SEMANTIC SEGMENTATION OF MINING FOOTPRINTS WITH MULTISPECTRAL SATELLITE IMAGERY
Muhamad Risqi Utama Saputra, Irfan Dwiki Bhaswara, Bahrul Ilmi Nasution, Monash University Indonesia, Indonesia; Michelle Ang Li Ern, University of Nottingham Malaysia, Malaysia; Nur Laily Romadhotul Husna, Tahjudil Witra, Vicky Feliren, Monash University Indonesia, Indonesia; John R. Owen, University of the Free State, South Africa; Deanna Kemp, The University of Queensland, Australia; Alex M. Lechner, Monash University Indonesia, Indonesia
Mon, 4 Aug, 16:15 - 16:30

MO4.M3.3: GDNet: A Graph Convolution and Hybrid Dilated Convolution Network for Road Extraction from High-resolution Satellite Images
Xiangan Zheng, China University of Geosciences, China; Jia Chen, Wuhan University of Science and Technology, China; Zhaozhao Zeng, Jun Li, China University of Geosciences, China
Mon, 4 Aug, 16:30 - 16:45

MO4.M3.4: Multi-Feature Sensing Decoder(MFSD): Advancing Remote Sensing Segmentation encoder
Dai Zirui, Beijing Institute of Technology, China; Bi Fukun, North China University of Technology, China
Mon, 4 Aug, 16:45 - 17:00

MO4.M3.5: CAMSDNET： CONSISTENCY-ASSISTED MULTI-SCALE DIFFERENCE-GUIDED NETWORK FOR REMOTE SENSING CHANGE DETECTION
Canbin Hu, Sida Du, Xiaokun Sun, College of Information Science and Technology, Beijing University of Chemical Technology, China, China