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Weed classification is a serious issue in the agricultural research. Weed classification is a necessity in identifying weed species for control. Many classification techniques have been used to identify weed based on images, however, most of the techniques only measure the percentages of accuracy but the detailed of classifier parameter are not analyzed and discussed. Therefore, in this work, feature...
In this paper, we explore the key factors in the design and implementation of visual computing (image processing and computer vision) algorithms on the massive parallel GPU (graphics processing units). The goal of the exploration is to provide common perspective and guidelines of using GPU for visual computing applications. We have selected three nontrivial applications (multiview stereo matching,...
We present a novel bottom-up saliency detection algorithm. Our method computes so-called local regression kernels (i.e., local features) from the given image, which measure the likeness of a pixel to its surroundings. Visual saliency is then computed using the said ldquoself-resemblancerdquo measure. The framework results in a saliency map where each pixel indicates the statistical likelihood of saliency...
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