DDF2Pol fuses real and complex domain features with attention to reach 98.16% OA on Flevoland and 96.12% on San Francisco PolSAR datasets using only 91k parameters.
Homayouni, PolSAR image classification based on deep con- volutional neural networks using wavelet transformation, IEEE Geoscience and Remote Sensing Letters 19 (2022) 1–5
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DDF2Pol: A Dual-Domain Feature Fusion Network for PolSAR Image Classification
DDF2Pol fuses real and complex domain features with attention to reach 98.16% OA on Flevoland and 96.12% on San Francisco PolSAR datasets using only 91k parameters.