TU3.R2: Deep Learning Methods for Inversion
Tue, 18 Jul, 13:00 - 14:15 Pacific Time (UTC -7)
Location: Room 2
Session Type: Oral
Session Chair: John Kerekes, Rochester Institute of Technology
Track: Data Analysis
Tue, 18 Jul, 13:00 - 13:12 Pacific Time (UTC -7)

TU3.R2.2: DYNAMIC RETRIEVAL OF OLIVE TREE PROPERTIES FROM SENTINEL-2 IMAGES USING AN RTM EMULATOR BASED ON ANN INVERSION AND A MULTI-SCALE VARIATIONAL METHOD.
Hana Abdelmoula, Sihem Chaabouni, Abdelaziz Kallel, CENTRE DE RECHERCHE EN NUMERIQUE DE SFAX, Tunisia; Achraf Makhloufi, ECOLE NATIONALE D'INGÉNIEURS DE SFAX, Tunisia; Ahmed Ben Ali, SOFRECOM, Tunisia; Mehrez Zribi, CESBIO, France
Tue, 18 Jul, 13:12 - 13:24 Pacific Time (UTC -7)

TU3.R2.3: DEEP LEARNING APPROACH FOR MICROWAVE INTERFEROMETRY IMAGE RECONSTRUCTION: APPLICATION TO THE SMOS SATELLITE

ALI KHAZAAL, RDIS Conseils, France; Richard Faucheron, Nemesio Rodriguez-Fernandez, Eric Anterrieu, CESBIO, France; Louise Yu, CNES, France
Tue, 18 Jul, 13:24 - 13:36 Pacific Time (UTC -7)

TU3.R2.4: TRANSFORMER AND CNN HYBRID NEURAL NETWORK FOR SEISMIC IMPEDANCE INVERSION
Chunyu Ning, Bangyu Wu, Xi'an Jiaotong University, China; Zhaolin Zhu, Hainan institute of Zhejiang University, China
Tue, 18 Jul, 13:36 - 13:48 Pacific Time (UTC -7)

TU3.R2.5: SPARSE DOA ESTIMATION BASED ON A DEEP UNFOLDED NETWORK FOR MIMO RADAR
Haoyang Tang, Yongchao Zhang, Jiawei Luo, Yin Zhang, Yulin Huang, Jianyu Yang, University of Electronic Science and Technology of China, China
Tue, 18 Jul, 13:48 - 14:03 Pacific Time (UTC -7)

TU3.R2.D: Discussion