About Us

This is just a sneak peek of everything that we can offer.

The Biometric & Pattern Recognition Research Group (Recogna), formerly known as the High-Performance Computing Laboratory, was established with the primary goal of advancing research in computer vision, machine learning, and biometrics. Our vision extends beyond pursuing state-of-the-art research; we also aim to cultivate a culture of collaborative research and teaching, fostering a passion for knowledge dissemination. If you relate with these principles and aspire to contribute to cutting-edge research in a collaborative environment, Recogna is the right place for you.

Members

This is Recogna's team, which counts with students and professors from several institutions.
Main Researchers
Aparecido Nilceu Marana
Clayton Reginaldo Pereira
João Paulo Papa
Kelton Augusto Pontara da Costa
Collaborators
Alexandre Falcão
Danilo Pereira
Edmond Ng
Patricia Bellin
Rodrigo Pisani
Willian Paraguassu
Post-doctoral Researchers
Claudio Santos
Danilo Jodas
Douglas Rodrigues
Leandro Passos Junior
Marcos Santana
Mateus Roder
Students
Arissa Yoshida
Master
Christian Barry
Undergraduate
Daniel Jangua
Master
Eduardo Monteiro
Undergraduate
Gabriel Garcia
PhD
Giovani Candido
PhD
João Correia
Master
João Frediani
Master
João Manesco
PhD
Kaio Paulo
Undergraduate
Luis Afonso
PhD
Luis Morelli
Master
Luiz Sementille
Master
Maria Miranda
Undergraduate
Maurício Zanella
Undergraduate
Milena Araujo
Undergraduate
Nicolas Gomes
Master
Nicole Gomes
Master
Pedro Paiola
PhD
Sofia Rosa
Undergraduate
Yasmin Sobrinho
Undergraduate
Alumni
André F.
Bárbara B.
Bruna R.
Caio C.
Daniel O.
Dheny F.
Gustavo B.
Gustavo R.
Lucas R.
Luis A.
Luis M.
Luiz C.
Nathalia Q.
Ricardo R.
Rodrigo Y.
Silas F.
Thierry M.

Tools

Glance at everything we have created so far.

LibOPF

LibOPF is a library of functions and programs for free usage in the design of optimum-path forest classifiers.

LibDEEP

LibDEEP is a C deep learning library for the development of artificial intelligence-based techniques.

LibOPT

LibOPT is a C optimization library for the development of metaheuristic-based techniques.

LibDEV

LibDEV is an integration library, built to assimilate LibOPF, LibDEEP and LibOPT together.

NALP

NALP is a Python easy-to-pack solution that covers natural adversarial language processing.

Opytimizer

Opytimizer is a Python library for the development of meta-heuristic optimization techniques.

OPFython

OPFython is a Python-inspired implementation of the Optimum-Path Forest classifier.

Learnergy

Learnergy is a Python-inspired package for the development of energy-based machine learning models.

Opytimark

Opytimark is a Python library consisting of optimization benchmarking functions.

Dualing

Dualing is a Python library that implements dual-based neural learning.

Textfier

Textfier provides an easier interface to text-based modifiers.

Statys

Statistical analyzers to provide more robust comparisons between Machine Learning techniques.

Datasets

Feel free to download our own datasets in order to work with our libraries. Also, it is possible to download other datasets already modelled to our file format. Please, remember to cite the appropriate references when using a specific dataset.

Biometric Recognition

Image Classification

Network Detection

Remote Sensing

Fake News Detection

Contact

Want to contact us? Just fill out the following form.