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We present a novel deep learning framework for crowd counting by learning a perspective-embedded deconvolution network. Perspective is an inherent property of most surveillance scenes. Unlike the traditional approaches that exploit the perspective as a separate normalization, we propose to fuse the perspective into a deconvolution network, aiming to obtain a robust, accurate and consistent crowd density...
A method for the segmentation of synthetic aperture radar (SAR) image is presented in this paper. The method integrates the use of multi-scale technology, mixed-model information and support vector machines (SVM). First, the multi-scale autoregressive (MAR) model is modeled for multi-scale sequence of SAR image, and a multi-scale features, which is used as input of SVM, are extracted via the MAR model...
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