no code implementations • 10 Sep 2022 • Fábio Mendonça, Sheikh Shanawaz Mostafa, Fernando Morgado-Dias, Antonio G. Ravelo-García
This work proposed kernel selection approaches for probabilistic classifiers based on features produced by the convolutional encoder of a variational autoencoder.
no code implementations • 4 Sep 2022 • Fábio Mendonça, Sheikh Shanawaz Mostafa, Fernando Morgado-Dias, Antonio G. Ravelo-García, Mário A. T. Figueiredo
ProBoost, a new boosting algorithm for probabilistic classifiers, is proposed in this work.
1 code implementation • 18 Dec 2021 • Fábio Mendonça, Sheikh Shanawaz Mostafa, Diogo Freitas, Fernando Morgado-Dias, Antonio G. Ravelo-García
The proposed approach is still in the upper range of the best state of the art works despite a difficult dataset, and has the advantage of providing a fully automatic analysis without requiring any manual procedure.