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An interesting target detection framework with transferred deep convolutional neural network (CNN) is proposed. For CNN, many labeled samples are needed to train the multi-layer network. However, for target detection tasks, only few target spectral signatures are available, or they are unknown in anomaly detection. In this work, we employ a reference data and further generate pixel-pairs to enlarge...
This paper reviews the state-of-the-art representation-based classification and detection approaches for hyperspectral remote sensing imagery, including sparse representation-based classification (SRC), collaborative representation-based classification (CRC), and their extensions. In addition to the original SRC and CRC, the related techniques are categorized into the following subsections: (1) representation-based...
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