TUP.P13.1

Physical Analysis of the Impact of Polarization Parameters on Deep-learning Networks for Nowcasting

Kexin Zhu, Haonan Chen, Colorado State University, United States; Lei Han, Ocean University of China, China
Session:
TUP.P13: Different Methods for Image Processing Poster
Track:
Data Analysis
Location:
Poster Area 13
Presentation Time:
Tue, 18 Jul, 14:15 - 15:45 Pacific Time (UTC -7)
Session Chair:
Joan Francesc Munoz-Martin, Jet Propulsion Laboratory / California Institute of Technology
Session Managers:
Ge Jiang and Lanying Wang and Ayoti Banerjee and Shubham Awasthi
Presentation
Discussion
Resources
No resources available.
Session TUP.P13
TUP.P13.1: Physical Analysis of the Impact of Polarization Parameters on Deep-learning Networks for Nowcasting
Kexin Zhu, Haonan Chen, Colorado State University, United States; Lei Han, Ocean University of China, China
TUP.P13.2: END-TO-END SHALLOW NETWORK FOR VARIATIONAL PANSHARPENING
Marc Tomás-Cruz, Jamila Mifdal, Bartomeu Coll, Joan Duran, Universitat de les Illes Balears, Spain
TUP.P13.3: Hybrid densely connected network for multi-exposure image fusion
Hao Zeng, Yulei Wang, Haoyang Yu, Meiping Song, Enyu Zhao, Tingting Tao, Dalian Maritime University, China
TUP.P13.4: A MULTI-LEVEL SUPERVISED NETWORK FOR PANSHARPENING TO REDUCE COLOR DISTORTION
Jian Guo, Ziyang Kong, Qizhi Xu, Beijing Institute of Technology, China
TUP.P13.5: A NERF-BASED COLOR CONSISTENCY METHOD FOR REMOTE SENSING IMAGES
Zongcheng Zuo, Yuanxiang Li, Tongtong Zhang, Shanghai Jiao Tong University, China
TUP.P13.6: SELF-SUPERVISED DENSE DEPTH ESTIMATION WITH PANORAMIC IMAGE AND SPARSE LIDAR
Chenwei Lyu, Huai Yu, Zhipeng Zhao, Wuhan University, China; Pengliang Ji, Beihang University, China; Xiangli Yang, Chongqing Jiaotong University, China; Wen Yang, Wuhan University, China
TUP.P13.7: A MULTISPECTRAL-INFRARED OBJECT DETECTION METHOD BASED ON CROSS-MODALITY IMAGE FEATURE FILTERING FUSION
Ze Liu, Nan Su, Chunhui Zhao, Yiming Yan, Harbin Engineering University, China
Resources
No resources available.