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Chi Zhang, Shiqing Wei, Shunping Ji and Meng Lu
The study investigates land use/cover classification and change detection of urban areas from very high resolution (VHR) remote sensing images using deep learning-based methods. Firstly, we introduce a fully Atrous convolutional neural network (FACNN) to...
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Xungen Li, Feifei Men, Shuaishuai Lv, Xiao Jiang, Mian Pan, Qi Ma and Haibin Yu
Vehicle detection in aerial images is a challenging task. The complexity of the background information and the redundancy of the detection area are the main obstacles that limit the successful operation of vehicle detection based on anchors in very-high-...
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Shuai Liu and Jialan Tang
Small object detection in very-high-resolution (VHR) optical remote sensing images is a fundamental but challenaging problem due to the latent complexities. To tackle this problem, the MdrlEcf model is proposed by modifying deep reinforcement learning (D...
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