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Scene Classification from Synthetic Aperture Radar Images Using Generalized Compact Channel-Boosted High-Order Orderless Pooling Network
2019
Remote Sensing
The convolutional neural network (CNN) has achieved great success in the field of scene classification. Nevertheless, strong spatial information in CNN and irregular repetitive patterns in synthetic aperture radar (SAR) images make the feature descriptors less discriminative for scene classification. Aiming at providing more discriminative feature representations for SAR scene classification, a generalized compact channel-boosted high-order orderless pooling network (GCCH) is proposed. The GCCH
doi:10.3390/rs11091079
fatcat:t2yskckmvjb7bk2ruh26puavuu