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Despite the availability of different algorithms for compression/decompression input images with the emergence of new technical issues of image compression is still relevant, as these tools allow you to assess the capabilities of existing mathematical apparatus that is used for image compression. In addition, the objective of image compression is vital in the design of combined neural networks with...
Remotely sensed images are composite images made of spectral bands ranging over Visible, Near Infrared, Middle Infrared and Far Infrared region of electromagnetic spectrum. Pixel based classification of high dimension multispectral images are complex, as the process takes lot of time and dataset is large. In this paper, Supervised Classification of Multispectral image is performed after band selection...
In this paper, we extend the neural network based approaches, which can asymptotically compute the largest or smallest eigenvalues and the corresponding eigenvectors of real symmetric matrix, to the real antisymmetric matrix case. Given any n-by-n real antisymmetric matrix, unlike the previous neural network based methods that were summarized by some ordinary differential equations (ODEs) with 2n...
Data classification is an intensively studied machine learning problem and there are two major categories of data classification algorithms, namely the logic based and the kernel based. The logic based classifiers, such as the decision tree and the rule-based classifier, feature the advantage of presenting a good summary about the distinctive characteristics of different classes of data. On the other...
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