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Deep Discriminative Representation Learning with Attention Map for Scene Classification
2020
Remote Sensing
In recent years, convolutional neural networks (CNNs) have shown great success in the scene classification of computer vision images. Although these CNNs can achieve excellent classification accuracy, the discriminative ability of feature representations extracted from CNNs is still limited in distinguishing more complex remote sensing images. Therefore, we propose a unified feature fusion framework based on attention mechanism in this paper, which is called Deep Discriminative Representation
doi:10.3390/rs12091366
fatcat:d56m3aeehzgcphnv4d6zniy5wi