Sitanshu Gupta

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Conventional clustering techniques like FCM, K-Means, Mountain clustering etc. face the main problem of excessive data while dealing with the very big size images. Due to higher order dependency of clustering techniques on the number of data points, time complexity increases excessively while dealing with very large size images. This paper proposes an(More)
The classification of speech into voiced and unvoiced is often a very important step in speech recognition and speaker identification systems. Even though several methods have been proposed for the same, the classification has been met with only moderately accurate results. In this paper, we propose the use of Support Vector Machines for classifying the(More)
Given a part of a document image taken with any camera at an arbitrary orientation and sometimes far-from-perfect illumination, an important problem is to match this query image to the corresponding full image from a document database. We propose a novel multi-resolution robust methodology for the same. The method combines information from independent(More)
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