54 citations · 208 across the 20 of their papers we have counts for
20 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…
Using deterministic tourist walk as a small-world metric on Watts-Strogatz networks
Joao V. Merenda, Odemir M. Bruno
The Watts-Strogatz model (WS) has been demonstrated to effectively describe real-world networks due to its ability to reproduce the small-world properties commonly observed in a va…
Exploring ordered patterns in the adjacency matrix for improving machine learning on complex networks
Mariane B. Neiva, Odemir M. Bruno
The use of complex networks as a modern approach to understanding the world and its dynamics is well-established in literature. The adjacency matrix, which provides a one-to-one re…
Improving Deep Neural Network Random Initialization Through Neuronal Rewiring
Leonardo Scabini, Bernard De Baets, Odemir M. Bruno
The deep learning literature is continuously updated with new architectures and training techniques. However, weight initialization is overlooked by most recent research, despite s…