Search Results for author: Alceu S. Britto Jr

Found 7 papers, 0 papers with code

Classifier Pool Generation based on a Two-level Diversity Approach

no code implementations3 Nov 2020 Marcos Monteiro, Alceu S. Britto Jr, Jean P. Barddal, Luiz S. Oliveira, Robert Sabourin

This paper describes a classifier pool generation method guided by the diversity estimated on the data complexity and classifier decisions.

Vocal Bursts Valence Prediction

A Comprehensive Comparison of End-to-End Approaches for Handwritten Digit String Recognition

no code implementations29 Oct 2020 Andre G. Hochuli, Alceu S. Britto Jr, David A. Saji, Jose M. Saavedra, Robert Sabourin, Luiz S. Oliveira

Over the last decades, most approaches proposed for handwritten digit string recognition (HDSR) have resorted to digit segmentation, which is dominated by heuristics, thereby imposing substantial constraints on the final performance.

object-detection Object Detection +1

Intrapersonal Parameter Optimization for Offline Handwritten Signature Augmentation

no code implementations13 Oct 2020 Teruo M. Maruyama, Luiz S. Oliveira, Alceu S. Britto Jr, Robert Sabourin

The method is used to generate offline signatures in the image and the feature space and train an ASVS.

Single-sample writers -- "Document Filter" and their impacts on writer identification

no code implementations18 May 2020 Fabio Pinhelli, Alceu S. Britto Jr, Luiz S. Oliveira, Yandre M. G. Costa, Diego Bertolini

The writing can be used as an important biometric modality which allows to unequivocally identify an individual.

Segmentation-Free Approaches for Handwritten Numeral String Recognition

no code implementations24 Apr 2018 Andre G. Hochuli, Luiz E. S. Oliveira, Alceu S. Britto Jr, Robert Sabourin

This paper presents segmentation-free strategies for the recognition of handwritten numeral strings of unknown length.

Segmentation

A Classifier-free Ensemble Selection Method based on Data Diversity in Random Subspaces

no code implementations13 Aug 2014 Albert H. R. Ko, Robert Sabourin, Alceu S. Britto Jr, Luiz E. S. Oliveira

Our scheme is the first ensemble selection method to be presented in the literature based on the concept of data diversity.

Clustering

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