3 papers
cs.CV2026
A self-supervised learning approach to deep filter banks for texture recognition
Joao B. Florindo, Lucas O. Lyra, Antonio E. Fabris
An important challenge in texture recognition is the limited amount of data for training frequently found in real-world applications. In computer vision in general, a successful st…
cs.CV2026
Deep neural networks with Fisher vector encoding for medical image classification
Lucas O. Lyra, Antonio E. Fabris, Joao B. Florindo
Orderless encoding methods have shown to improve Convolutional Neural Networks (CNNs) for image classification in the context of limited availability of data. Additionally, hybrid…
cs.CV2022
Multilayer deep feature extraction for visual texture recognition
Lucas O. Lyra, Antonio Elias Fabris, Joao B. Florindo
Convolutional neural networks have shown successful results in image classification achieving real-time results superior to the human level. However, texture images still pose some…