Remote sensing-enhanced transfer learning approach for agricultural damage and change detection: A deep learning perspective
Zehua LiuCollege of Water Conservancy and Civil Engineering, South China Agricultural University, Guangzhou 510642, ChinaJiuhao LiCollege of Water Conservancy and Civil Engineering, South China Agricultural University, Guangzhou 510642, ChinaMahmood AshrafSchool of Microelectronics and Communication Engineering, Chongqing University, Chongqing, ChinaSyam M.S.Guangdong-Hong Kong-Macao GBA New Generation Intelligent IoT Research Center, Shenzhen University, Guangdong, Shenzhen, China 518060Muhammad AsifSchool of Media, Hunan University of Science and Engineering, 425199 Yongzhou, Hunan, ChinaEmad Mahrous AwwadDepartment of Electrical Engineering, College of Engineering, King Saud University, P.O. Box 800, Riyadh 11421, Saudi ArabiaMuna Al‐RazganDepartment of Software Engineering, College of Computer and Information Sciences, King Saud University, P.O. Box 22452, Riyadh 11495, Saudi ArabiaUzair Aslam BhattiSchool of Information and Communication Engineering, Hainan University, Haikou, China
2024en
ABI
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