Fusion of complex networks and randomized neural networks for texture analysis
Bruno, Odemir Martinez
2020LA Referencia (Red Federada de Repositorios Institucionales de Publicaciones Científicas)28 citationsDOIOpen Access PDF
Abstract
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 network and its topological properties as well as the image pixels are used to train randomized neural networks to create a signature that represents the deep characteristics of the texture. The results obtained surpassed the accuracy of many methods available in the literature. This performance demonstrates that our proposed approach opens a promising source of research, which consists of exploring the synergy of neural networks and complex networks in the texture analysis field.
Topics & Concepts
Artificial neural networkArtificial intelligenceComputer scienceDiscriminative modelPattern recognition (psychology)Texture (cosmology)Image (mathematics)PixelSignature (topology)Computer visionMathematicsGeometryImage Retrieval and Classification TechniquesAdvanced Image and Video Retrieval TechniquesRemote-Sensing Image Classification