WE3.R3.4

SYNTHETIC CLOUD HEIGHT PREDICTION USING STEREO MATCHING AND DEEP LEARNING

Rabin Dhakal, Chad Mourning, Ohio University, United States
Session:
WE3.R3: Extracting Features for Optical Data Oral
Track:
Data Analysis
Location:
Marinos
Presentation Time:
Wed, 10 Jul, 15:22 - 15:36
Session Co-Chairs:
Mauro Dalla Mura, Grenoble INP and Yu Zhao, KTH Royal Institute of Technology
Presentation
Discussion
Resources
No resources available.
Session WE3.R3
WE3.R3.1: LOCAL REPRESENTATION LEARNING USING VISUAL PRIORS FOR REMOTE SENSING
Viktor Brack, Dominik Koßmann, TU Dortmund University, Germany
WE3.R3.2: NEURAL EMBEDDING COMPRESSION FOR EFFICIENT MULTI-TASK EARTH OBSERVATION MODELLING
Carlos Gomes, Thomas Brunschwiler, IBM Research - Europe, Switzerland
WE3.R3.3: Feature-Domain Fidelity and Tensor Low-Rank Regularization for Cloud Removal in Remote Sensing Images
Wen-Jie Zheng, Xiao-Xuan Bai, University of Electronic Science and Technology of China, China; Yu-Bang Zheng, Southwest Jiaotong University, China; Ya-Ru Fan, Southwest Minzu University, China; Ting-Zhu Huang, Xi-Le Zhao, University of Electronic Science and Technology of China, China
WE3.R3.4: SYNTHETIC CLOUD HEIGHT PREDICTION USING STEREO MATCHING AND DEEP LEARNING
Rabin Dhakal, Chad Mourning, Ohio University, United States
WE3.R3.5: TOWARDS MULTI-TASK HEIGHT ESTIMATION FROM MONOCULAR REMOTE SENSING IMAGERY
Houda Chaabouni-Chouayakh, Sm@rts Laboratory, Digital Research Center of Sfax, Tunisia; Mariem Oualha, Sup'Com, Tunisia; Hossein Arefi, Mainz University of Applied Sciences, Germany; Abdelaziz Kallel, Sm@rts Laboratory, Digital Research Center of Sfax, Tunisia
WE3.R3.6: Nonlinear Unmixing of Hyperspectral Images via Regularized Wasserstein Dictionary Learning
Scott Fullenbaum, Marshall Mueller, Abiy Tasissa, James Murphy, Tufts University, United States
WE3.R3.7: RETHINKING HYPERSPECTRAL IMAGE THREE-DIMENSIONAL FEATURE EXTRACTION WITH SINGULAR SPECTRUM ANALYSIS
Hang Fu, Aizhu Zhang, Cheng Jing, Genyun Sun, China University Of Petroleum, China
Resources
No resources available.