80 citations · 130 across the 6 of their papers we have counts for
5 papers · 1 filter
HiPerViT: A Hierarchical Perceiver-Vision Transformer Architecture for Multi-Scale Texture Recognition
João Pedro C. A. de Sá, Odemir Martinez Bruno
Texture recognition remains challenging for modern vision models because discriminative evidence is often carried by higher-order spatial statistics rather than by object shape alo…
VORTEX: Challenging CNNs at Texture Recognition by using Vision Transformers with Orderless and Randomized Token Encodings
Leonardo Scabini, Kallil M. Zielinski, Emir Konuk +4
Texture recognition has recently been dominated by ImageNet-pre-trained deep Convolutional Neural Networks (CNNs), with specialized modifications and feature engineering required t…
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)…
Evaluation of Activated Sludge Settling Characteristics from Microscopy Images with Deep Convolutional Neural Networks and Transfer Learning
Sina Borzooei, Leonardo Scabini, Gisele Miranda +7
Microbial communities play a key role in biological wastewater treatment processes. Activated sludge settling characteristics, for example, are affected by microbial community comp…