80 citations · 89 across the 11 of their papers we have counts for
11 papers
A Comparative Survey of Vision Transformers for Feature Extraction in Texture Analysis
Leonardo Scabini, Andre Sacilotti, Kallil M. Zielinski +3
Texture, a significant visual attribute in images, has been extensively investigated across various image recognition applications. Convolutional Neural Networks (CNNs), which have…
Advanced wood species identification based on multiple anatomical sections and using deep feature transfer and fusion
Kallil M. Zielinski, Leonardo Scabini, Lucas C. Ribas +5
In recent years, we have seen many advancements in wood species identification. Methods like DNA analysis, Near Infrared (NIR) spectroscopy, and Direct Analysis in Real Time (DART)…
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…
A Network Classification Method based on Density Time Evolution Patterns Extracted from Network Automata
Kallil M. C. Zielinski, Lucas C. Ribas, Jeaneth Machicao +1
Network modeling has proven to be an efficient tool for many interdisciplinary areas, including social, biological, transport, and many other real world complex systems. In additio…
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…
Social Interaction Layers in Complex Networks for the Dynamical Epidemic Modeling of COVID-19 in Brazil
Leonardo F. S. Scabini, Lucas C. Ribas, Mariane B. Neiva +3
We are currently living in a state of uncertainty due to the pandemic caused by the Sars-CoV-2 virus. There are several factors involved in the epidemic spreading such as the indiv…
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…
Texture analysis using deterministic partially self-avoiding walk with thresholds
Lucas Correia Ribas, Wesley Nunes Gonçalves, Odemir Martinez Bruno
In this paper, we propose a new texture analysis method using the deterministic partially self-avoiding walk performed on maps modified with thresholds. In this method, two pixels…
Fast deterministic tourist walk for texture analysis
Lucas Correia Ribas, Odemir Martinez Bruno
Deterministic tourist walk (DTW) has attracted increasing interest in computer vision. In the last years, different methods for analysis of dynamic and static textures were propose…