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SAR Target Recognition Based on Cross-Domain and Cross-Task Transfer Learning
2019
IEEE Access
Inspired by their tremendous success in optical image detection and classification, convolutional neural networks (CNNs) have recently been used in synthetic aperture radar automatic target recognition (SAR-ATR). Although CNN-based methods can achieve excellent recognition performance, it is difficult to collect a large number of real SAR images available for training. In this paper, we introduce simulated SAR data to alleviate the problem of insufficient training data. To address domain shift
doi:10.1109/access.2019.2948618
fatcat:3mql7wr6nzgnfhxvhgvmdipium