Ricardo T. Fares

According to our database, Ricardo T. Fares authored at least 9 papers between 2024 and 2026.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of five.

2026

VORTEX: Challenging CNNs at texture recognition by using vision transformers with orderless and randomized token encodings.

Leonardo F. S. Scabini, Kallil M. C. Zielinski, Emir Konuk, Ricardo T. Fares, Lucas Correia Ribas, Kevin Smith, Odemir M. Bruno

Neurocomputing, 2026

Complex networks for modeling texture and spectral features of hyperspectral images for environmental analysis.

Leonardo F. S. Scabini, Kallil M. C. Zielinski, Marilia Fernandes, Ricardo T. Fares, Lucas Correia Ribas, Rosana Marta Kolb, Odemir M. Bruno

Comput. Biol. Medicine, 2026

2025

MIXER: Mixed Hyperspherical Random Embedding Neural Network for Texture Recognition.

Ricardo T. Fares, Lucas Correia Ribas

CoRR, October, 2025

Volumetric Color-Texture Representation for Colorectal Polyp Classification in Histopathology Images.

Ricardo T. Fares, Lucas Correia Ribas

Proceedings of the 20th International Joint Conference on Computer Vision, 2025

Exploring Local Graphs via Random Encoding for Texture Representation Learning.

Ricardo T. Fares, Luan B. Guerra, Lucas Correia Ribas

Proceedings of the 20th International Joint Conference on Computer Vision, 2025

2024

Randomized Encoding Ensemble: A New Approach for Texture Representation.

Ricardo T. Fares, Ana Catarina M. Vicentim, Leonardo F. S. Scabini, Kallil M. C. Zielinski, Rachid Jennane, Odemir M. Bruno, Lucas Correia Ribas

Proceedings of the 31st International Conference on Systems, Signals and Image Processing, 2024

Randomized Autoencoder-based Representation for Dynamic Texture Recognition.

Ricardo T. Fares, Lucas Correia Ribas

Proceedings of the 31st International Conference on Systems, Signals and Image Processing, 2024

Deep Texture Feature Aggregation on Leaf Microscopy Images for Brazilian Plant Species Recognition.

Leonardo F. S. Scabini, Kallil M. C. Zielinski, Ricardo T. Fares, Emir Konuk, Gisele Miranda, Rosana Marta Kolb, Lucas Correia Ribas, Odemir M. Bruno

Proceedings of the 2024 9th International Conference on Machine Learning Technologies, 2024

A New Approach to Learn Spatio-Spectral Texture Representation with Randomized Networks: Application to Brazilian Plant Species Identification.

Ricardo T. Fares, Lucas Correia Ribas

Proceedings of the Engineering Applications of Neural Networks, 2024