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In this paper, convolutional neural networks (CNNs) is employed for remote-sensing scene classification, which fully utilizes the semantic features extracted from the images while ignoring some traditional features. Consider the limited labeled samples, CaffeNet model as the pre-trained architecture is adopted. By fine-tuning the pre-trained models, the proposed method is expected to be robust and...
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