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In this paper, we study the problem of fine-grained image categorization, which is much more useful in real applications than basic image classification. Based on the most challenge dataset, CUB-200, we combine Efficient match kernel (EMK) with the weighted spatial pyramid to achieve state-of-art performance. Comparison with BoW, which can also be viewed as kernel matching approach, EMK digs the relations...
Texture classification is a classical yet still active topic in computer vision and pattern recognition. Recently, several new texture classification approaches by modeling texture images as distributions over a set of textons have been proposed. These textons are learned as the cluster centers in the image patch feature space using the K-means clustering algorithm. However, the Euclidian distance...
Recently, there has been a dramatic increase of the amount of audio, video, and images created and shared on the Internet by users around the world. Much of this content is publicly available and free of cost. When viewed through the lens of pattern classification, this content can be seen as a virtually unlimited supply of training data for various statistical modeling and labeling tasks such as...
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