TQ-L.B.3
LOW SNR MULTIFRAME REGISTRATION FOR CUBESATS
Evan Widloski, Farzad Kamalabadi, University of Illinois Urbana-Champaign, United States of America
Session:
Computational Imaging Methods and Models
Track:
Computational Imaging Methods and Models
Location:
Room B
Presentation Time:
Tue, 18 Oct, 20:30 - 20:45 China Standard Time (UTC +8)
Tue, 18 Oct, 14:30 - 14:45 Central European Time (UTC +2)
Tue, 18 Oct, 12:30 - 12:45 UTC
Tue, 18 Oct, 08:30 - 08:45 Eastern Time (UTC -4)
Tue, 18 Oct, 14:30 - 14:45 Central European Time (UTC +2)
Tue, 18 Oct, 12:30 - 12:45 UTC
Tue, 18 Oct, 08:30 - 08:45 Eastern Time (UTC -4)
Session Chair:
Jean-François Aujol, U Bordeaux
Presentation
Discussion
Resources
No resources available.
Session TQ-L.B
TQ-L.B.1: BINARY MORPHOLOGICAL NEURAL NETWORK
Theodore Aouad, Hugues Talbot, CentraleSupelec, Université Paris-Saclay, Inria, France
TQ-L.B.2: INFRARED AND VISIBLE IMAGE FUSION USING BIMODAL TRANSFORMERS
Seonghyun Park, An Gia Vien, Chul Lee, Dongguk University, Korea, Republic of
TQ-L.B.3: LOW SNR MULTIFRAME REGISTRATION FOR CUBESATS
Evan Widloski, Farzad Kamalabadi, University of Illinois Urbana-Champaign, United States of America
TQ-L.B.4: UNDERSAMPLED DYNAMIC FOURIER PTYCHOGRAPHY VIA PHASELESS PCA
Zhengyu Chen, Seyedehsara Nayer, Namrata Vaswani, Iowa State University, United States of America
TQ-L.B.5: DISTRIBUTED RADAR AUTOFOCUS IMAGING USING DEEP PRIORS
Hassan Mansour, Suhas Lohit, Petros Boufounos, Mitsubishi Electric Research Laboratories, United States of America