Technical Program: Paper Detail || IGARSS 2023 || Pasadena, California, USA || 16

TU4.R14.1

A NEW APPROACH FOR DOWNSCALING SOIL MOISTURE BY MERGING CONDITIONAL ADVERSARIAL NETWORKS AND PHYSICS-BASED PASSIVE MICROWAVE RETRIEVAL

Archana Kannan, University of Southern California, United States; Grigorios Tsagkatakis, Foundation for Research and Technology-Hellas (FORTH), Greece; Mahta Moghaddam, University of Southern California, United States

Session:

TU4.R14: Machine Learning for Image Processing and Synthesis Oral

Location:

Room E

Presentation Time:

Tue, 18 Jul, 15:45 - 15:57 Pacific Time (UTC -7)

Session Chair:

Ilke Demir, Intel Labs

Session Manager:

Ayoti Banerjee

Session TU4.R14

TU4.R14.1: A NEW APPROACH FOR DOWNSCALING SOIL MOISTURE BY MERGING CONDITIONAL ADVERSARIAL NETWORKS AND PHYSICS-BASED PASSIVE MICROWAVE RETRIEVAL

TU4.R14.2: DEEPFAKE SATELLITE IMAGERY DETECTION WITH MULTI-ATTENTION AND SUPER RESOLUTION

Umur Aybars Ciftci, Binghamton University, United States; Ilke Demir, Intel Labs, United States

TU4.R14.3: EFFICIENT AND RELIABLE QUANTILE APPROXIMATION FOR LARGE-SCALE EARTH OBSERVATION USING T-DIGEST

Michael Engel, Technical University of Munich, Germany; Adrián Luna Cobos, European Union Satellite Centre, Spain; Matej Batic, Sinergise Laboratory for Geographical Information Systems LTD., Slovenia; Marco Körner, Technical University of Munich, Germany

TU4.R14.4: BLIND SINGLE IMAGE-BASED THIN CLOUD REMOVAL USING CLOUD PERCEPTION INTEGRATED FOURIER CONVOLUTION NETWORK

Yujun Guo, Wei He, Hongyan Zhang, Wuhan University, China

TU4.R14.5: A MACHINE LEARNING APPROACH FOR HIGH RESOLUTION FRACTIONAL VEGETATION COVER ESTIMATION USING PLANET CUBESAT AND RGB DRONE DATA FUSION

Jacob Nesslage, Brittany Lopez Barreto, Adam Weingram, Erin Hestir, University of California, Merced, United States