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Human detection is a complex problem owing to the variable pose that they can adopt. Here, we address this problem in sparse representation framework with an overcomplete scale-embedded dictionary. Histogram of oriented gradient features extracted from the candidate image patches are sparsely represented by the dictionary that contain positive bases along with negative and trivial bases. The object...
The problem of human detection is challenging, more so, when faced with adverse conditions such as occlusion and background clutter. This paper addresses the problem of human detection by representing an extracted feature of an image using a sparse linear combination of chosen dictionary atoms. The detection along with the scale finding, is done by using the coefficients obtained from sparse representation...
Mining consumer-generated text can provide business intelligence to organizations by extracting important knowledge trapped in the form of opinions, thoughts, and ideas expressed by their employees and customers on various aspects relevant to business. The key challenge here is to extract and organize relevant information from noisy text in order to effectively transform it to actionable intelligence...
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