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Recently, Convolutional Neural Networks (CNNs) have been used for the classification of hand activities from surface Electromyography (sEMG) signals. However, sEMG signal has spatial sparsity due to position of electrodes on hand muscle and temporal dependency due to performance of activity over a period of time. The CNN has the ability to extract spatial features and is limited in extracting temporal...
Computational technology advancements have enabled the radar engineers to model and understand extended targets. One of the common statistical models of extended target is based on Gaussian distribution. In this paper, we address the problem of detection of such an extended target that has a non-Gaussian clutter plus noise background using MIMO radar. Specifically, approximations are sought for theoretically...
Content Based Image Retrieval (CBIR) deals withthe automatic extraction of images from a database based ona query. For efficient retrieval the digital image CBIR requiressupport of scene classification algorithms. The Cognitive psychology suggests that the basic level classification is efficient withthe global features. However, a detailed classification requires acombination of the global and the...
Our research objective is to develop a supervised learning based hierarchical classification framework built upon Gabor features. Specifically, we experimented on the Oliva Tor alba data-set from the Corel stock photo library. This data set consists of 2688 natural and artificial scene color images, of size (256X256X3) each, from 8 sub-categories. In this paper, we restrict our goal to categorization...
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