Kesari Verma

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The contiguous sequences of the terms (N-grams) in the documents are symmetrically distributed among different classes. The symmetrical distribution of the N-Grams raises uncertainty in the belongings of the N-Grams towards the class. In this paper, we focused on the selection of most discriminating N-Grams by reducing the effects of symmetrical(More)
The selection of most informative terms reduces the feature set and speed up the classification process. The most informative terms are highly affected by the correlative association of the terms. The rare terms are most informative than sparse and common terms. The main objective of this study is assigning a higher weight to the rare terms and less weight(More)
— Classification of the physical properties of sonar targets is one of the difficult tasks. The increased use of sonar motivated the researcher to produce cost effective and automated process for classification. Neural Network and Online Multiple Kernel Learning (OMKL), that aims to learn a kernel based prediction function from a pool of predefined kernels(More)
An ultrasound image provides the radiologist with noninvasive, low cost, and real-time images that can help them in diagnosis, planning and therapy. However low PSNR (picture signal to noise ratio) in ultrasound images causes difficulties in correct interpretation of ultrasound images. Further speckle noise present in ultrasound images is considered to be(More)
Association rule mining is one of the important problems of data mining. Single minimum support based approaches of association rule mining suffers from "rare item problem". An improved approach MSApriori uses multiple supports to generate association rules that consider rare item sets. Necessity to first identify the "large" set of items contained in the(More)
In this paper, a new technique for facial expression recognition is proposed which uses the statistical feature of the whole face and classify the expression using neural network classifier. When the face image is input, region of interest (ROI) is being obtained to evaluate the statistical feature of the face. Using these, features we classify the face(More)
Face detection is one of the important problem of image processing and pattern recognition. Most of the existing algorithm takes the frame of fixed size in order to detect the faces in any image. In any image it is possible that the image that are near are larger in size in comparison to the faces that are in back side. In this paper we proposed a novel(More)
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