Brazilian Sign Language Recognition

One challenge in Brazilian Sign Language (Libras) recognition is the absence of a robust dataset that allows the validation of different methodologies. For this aim, our team developed two datasets, which we are using with different Machine Learning techniques to help deaf developing communication with deaf people and human-computer interaction based on visual signs. The first dataset contains 10 recorded signs and the second one 20 signs. Read more to joining us.

Integrating Q-Learning in Adaptive Large Neighborhood Search Metaheuristic for the Parallel Machine Scheduling

An important scheduling problem is dealt in this project. The unrelated parallel machine scheduling with the objective to minimize the makespan is addressed. This problem has a set of non-preemptive jobs and a set of machines with the following characteristics: i) Each job is allocated to only one machine; ii) There is a processing time to complete each job in a machine; iii) There is a setup time that depends on the sequence of the allocation of the jobs in the machines. The objectives involve allocating all jobs in the machines, minimizing the makespan (or the maximum completion time of the scheduling).

pyFTS - Fuzzy Time Series for Python

Python library for Fuzzy Time Series

Data Visualization in Many Objective Optimization Problems (MaOPs)

Data Visualization in high-dimensional spaces is a great challenge and an important tool for decision-making. The method of Aggregation Trees was an important step in visualization in MaOPs, allowing a greater understanding of the problem. This method is based on the sequential aggregation of objectives, which is visually represented into a tree, based on a measure of conflict between pairs of (groups of) objectives. The method allows the visualization of a hierarchy for aggregation of the objectives, with possibility to create new constraints for the problem or reduce the number of objectives in a further analysis (Silva2016).