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In this paper, we address the problem of natural flower classification. It is a challenging task due to the non-rigid deformation, illumination changes, and inter-class similarity. We build a large dataset of flower images in the wide with 79 categories and propose a novel framework based on convolutional neural network (CNN) to solve this problem. Unlike other methods using hand-crafted visual features,...
Visual Object tracking is one of the key problems is machine vision. A contourlet transform based visual object tracking method is given in this paper. Being one of the multi-scale geometric analysis methods, the contourlet transform has better performance than the traditional wavelet transform to describe the edge feature of visual objects. The contourlet coefficients are firstly obtained and parts...
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