FR3.R1.1: CONTEXTUAL CLASSIFICATION OF POLARIMETRIC SAR DATA THROUGH A COMPLEX-VALUED KERNEL AND GLOBAL ENERGY MINIMIZATION
Ignacio Masari, Gabriele Moser, Sebastiano Serpico, University of Genoa, Italy
FR3.R1.3: COMPLEX-VALUED FULLY CONVOLUTIONAL NETWORK FOR PolSAR IMAGE CLASSIFICATION WITH NOISY LABELS
Ningwei Wang, Xi’an Jiaotong University, China; Haixia Bi, Xiaotian Wang, Xi'an Jiaotong University, China; Zhao Chen, Donghua University, China
FR3.R1.4: Wishart-UMAP - Translating Pixel Similarity of PolSAR Images to Real-valued Feature Descriptors
Sylvia Hochstuhl, Karlsruhe Institute of Technology, Germany; Horst Hammer, Fraunhofer IOSB, Germany; Antje Thiele, Stefan Hinz, Karlsruhe Institute of Technology, Germany
FR3.R1.5: NOISE-TOLERANT UNSUPERVISED CLASSIFICATION FOR POLSAR IMAGES VIA DEEP CLUSTERING AND MARKOV RANDOM FIELD
Sihan Yang, Haixia Bi, Xiaotian Wang, Xi'an Jiaotong University, China; Danfeng Hong, Chinese Academy of Sciences, China