227 citations · 794 across the 65 of their papers we have counts for
30 papers · 1 filter
RADAM: Texture Recognition through Randomized Aggregated Encoding of Deep Activation Maps
Leonardo Scabini, Kallil M. Zielinski, Lucas C. Ribas +3
Texture analysis is a classical yet challenging task in computer vision for which deep neural networks are actively being applied. Most approaches are based on building feature agg…
Learning Local Complex Features using Randomized Neural Networks for Texture Analysis
Lucas C. Ribas, Leonardo F. S. Scabini, Jarbas Joaci de Mesquita Sá Junior +1
Texture is a visual attribute largely used in many problems of image analysis. Currently, many methods that use learning techniques have been proposed for texture discrimination, a…
Spatio-spectral networks for color-texture analysis
Leonardo F. S. Scabini, Lucas C. Ribas, Odemir M. Bruno
Texture is one of the most-studied visual attribute for image characterization since the 1960s. However, most hand-crafted descriptors are monochromatic, focusing on the gray scale…
Dynamic texture analysis with diffusion in networks
Lucas C. Ribas, Wesley N. Goncalves, Odemir M. Bruno
Dynamic texture is a field of research that has gained considerable interest from computer vision community due to the explosive growth of multimedia databases. In addition, dynami…
Fusion of complex networks and randomized neural networks for texture analysis
Lucas C. Ribas, Jarbas J. M. Sa Junior, Leonardo F. S. Scabini +1
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 model…
Multilayer Complex Network Descriptors for Color-Texture Characterization
Leonardo F S Scabini, Rayner H M Condori, Wesley N Gonçalves +1
A new method based on complex networks is proposed for color-texture analysis. The proposal consists on modeling the image as a multilayer complex network where each color channel…