activity
20152022
most citedLearning Features for Offline Handwritten Signature Verification using Deep Convolutional Neural Networks

387 citations · 450 across the 10 of their papers we have counts for

collaborators

36 papers

cs.LG2022

Dynamic Ensemble Selection Using Fuzzy Hyperboxes

Reza Davtalab, Rafael M. O. Cruz, Robert Sabourin

Most dynamic ensemble selection (DES) methods utilize the K-Nearest Neighbors (KNN) algorithm to estimate the competence of classifiers in a small region surrounding the query samp…

cs.LG2020

Classifier Pool Generation based on a Two-level Diversity Approach

Marcos Monteiro, Alceu S. Britto, Jean P. Barddal +2

This paper describes a classifier pool generation method guided by the diversity estimated on the data complexity and classifier decisions. First, the behavior of complexity measur…

cs.CV2020

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

Andre G. Hochuli, Alceu S. Britto, David A. Saji +3

Over the last decades, most approaches proposed for handwritten digit string recognition (HDSR) have resorted to digit segmentation, which is dominated by heuristics, thereby impos…

cs.CV2020

An Investigation of Feature Selection and Transfer Learning for Writer-Independent Offline Handwritten Signature Verification

Victor L. F. Souza, Adriano L. I. Oliveira, Rafael M. O. Cruz +1

SigNet is a state of the art model for feature representation used for handwritten signature verification (HSV). This representation is based on a Deep Convolutional Neural Network…

cs.CV2020

Intrapersonal Parameter Optimization for Offline Handwritten Signature Augmentation

Teruo M. Maruyama, Luiz S. Oliveira, Alceu S. Britto +1

Usually, in a real-world scenario, few signature samples are available to train an automatic signature verification system (ASVS). However, such systems do indeed need a lot of sig…

cs.LG20202 cited

Random Forest for Dissimilarity-based Multi-view Learning

Simon Bernard, Hongliu Cao, Robert Sabourin +1

Many classification problems are naturally multi-view in the sense their data are described through multiple heterogeneous descriptions. For such tasks, dissimilarity strategies ar…