TH1.R14.3

Automatic simulation of SAR images: comparing a deep-learning based method to a hybrid method.

Nathan Letheule, Flora Weissgerber, ONERA, France; Sylvain Lobry, LIPADE, Université de Paris, Paris, France, France; Elise Colin, ONERA, France
Session:
TH1.R14: SAR and Machine Learning Oral
Track:
AI and Big Data
Location:
Room E
Presentation Time:
Thu, 20 Jul, 08:54 - 09:06 Pacific Time (UTC -7)
Session Co-Chairs:
Ronny Hänsch, German Aerospace Center and Kelsey Doerksen, University of Oxford
Session Manager:
Ayoti Banerjee
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Session TH1.R14
TH1.R14.1: SALIENCY-GUIDED ATTENTION-BASED FEATURE PYRAMID NETWORK FOR SHIP DETECTION IN SAR IMAGES
Tianwen Zhang, Xiaoling Zhang, Zikang Shao, University of Electronic Science and Technology of China, China
TH1.R14.2: A HIGH ACCURACY DETECTION NETWORK FOR ROTATED MULTI-CLASS SAR SHIP DETECTION
Zikang Shao, Xiaoling Zhang, University of Electronic Science and Technology of China, China
TH1.R14.3: Automatic simulation of SAR images: comparing a deep-learning based method to a hybrid method.
Nathan Letheule, Flora Weissgerber, ONERA, France; Sylvain Lobry, LIPADE, Université de Paris, Paris, France, France; Elise Colin, ONERA, France
TH1.R14.4: IS REALISTIC SYNTHETIC INSAR DATA GENERATION FEASIBLE ON LOW DATA REGIMES?
Nikolaos Ioannis Bountos, Ioannis Papoutsis, Orion Lab, Institute for Astronomy, Astrophysics, Space Applications, and Remote Sensing, National Observatory of Athens, Greece; Dimitrios Michail, Harokopio University of Athens, Greece
TH1.R14.5: PRECIPITATION-TRIGGERED LANDSLIDE PREDICTION IN NEPAL USING MACHINE LEARNING AND DEEP LEARNING
Kelsey Doerksen, Yarin Gal, Freddie Kalaitzis, University of Oxford, United Kingdom; Cristian Rossi, Satellite Applications Catapult, United Kingdom; David Petit, Deimos Space, United Kingdom; Sihan Li, University of Sheffield, United Kingdom; Simon Dadson, University of Oxford, United Kingdom
Resources
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