TH1.R6.4

DEEP LEARNING FRAMEWORK FOR MULTI-PHYSICS JOINT INVERSION AND ITS APPLICATION IN THE DECORAH AREA

Yanyan Hu, University of Houston, United States; Xiaolong Wei, Stanford University, United States; Xuqing Wu, Jiajia Su, Yueqin Huang, Jiefu Chen, University of Houston, United States
Session:
TH1.R6: Physics-aware Machine Learning and Explainability Oral
Track:
AI and Big Data
Location:
Skalkotas Hall
Presentation Time:
Thu, 11 Jul, 09:42 - 09:56
Session Co-Chairs:
Yuanyuan Wang, Technical University of Munich and James Koch, Pacific Northwest National Laboratory
Presentation
Discussion
Resources
No resources available.
Session TH1.R6
TH1.R6.1: MANIFOLD-BASED SHAPLEY FOR SAR RECOGNIZATION NETWORK EXPLANATION
Xuran Hu, Mingzhe Zhu, Yuanjing Liu, Zhengpeng Feng, Xidian University, China; LJubisa Stankovic, University of Montenegro, Montenegro
TH1.R6.2: EXPLORING THE EXPLAINABILITY OF SAR TARGET CLASSIFICATION USING SHAP METHOD WITH DIFFERENT BASELINE VALUES
Zhiyuan Yang, Zongyong Cui, Zongjie Cao, University of Electronic Science and Technology of China School of Information and Communication, China
TH1.R6.3: EDGE COMPLEMENTARY MULTI-SCALE AGGREGATION NETWORK FOR SALIENT OBJECT DETECTION IN OPTICAL REMOTE SENSING IMAGES
Bei Cheng, Zao Liu, Chengbiao Fu, Tao Shen, Kunming University of Science and Technology, China
TH1.R6.4: DEEP LEARNING FRAMEWORK FOR MULTI-PHYSICS JOINT INVERSION AND ITS APPLICATION IN THE DECORAH AREA
Yanyan Hu, University of Houston, United States; Xiaolong Wei, Stanford University, United States; Xuqing Wu, Jiajia Su, Yueqin Huang, Jiefu Chen, University of Houston, United States
TH1.R6.5: Physics-informed Machine Learning for Deep Ice Layer Tracing in SAR images
Maryam Rahnemoonfar, Ben Zalatan, Lehigh University, United States
TH1.R6.6: Data-Driven Invertible Neural Surrogates of Atmospheric Transmission
James Koch, Brenda Forland, Bruce Bernacki, Tim Doster, Tegan Emerson, Pacific Northwest National Laboratory, United States
TH1.R6.7: TRANSFERABLE PHYSICAL ADVERSARIAL PATCH ATTACK FOR REMOTE SENSING OBJECT DETECTION
Di Wang, Wenxuan Zhu, Ke Li, Xidian University, China; Xiao Gao, Xi’an University of Architecture and Technology, China; Pengfei Yang, Xidian University, China
Resources
No resources available.