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Fusion of complex networks and randomized neural networks for texture analysis
[article]
2020
arXiv
pre-print
This paper presents a high discriminative texture analysis method based on the fusion of complex networks and randomized neural networks. In this approach, the input image is modeled as a complex networks and its topological properties as well as the image pixels are used to train randomized neural networks in order to create a signature that represents the deep characteristics of the texture. The results obtained surpassed the accuracies of many methods available in the literature. This
arXiv:1806.09170v2
fatcat:wgmnsxiqmvcljc4ly4whdlonpe