activity
20162020
most citedLearning Features for Offline Handwritten Signature Verification using Deep Convolutional Neural Networks

387 citations · 446 across the 6 of their papers we have counts for

collaborators
Showing 2018Show all

5 papers · 1 filter

cs.CV2018

Decoupling Direction and Norm for Efficient Gradient-Based L2 Adversarial Attacks and Defenses

Jérôme Rony, Luiz G. Hafemann, Luiz S. Oliveira +3

Research on adversarial examples in computer vision tasks has shown that small, often imperceptible changes to an image can induce misclassification, which has security implication…

cs.CV2018

The Impact of Preprocessing on Deep Representations for Iris Recognition on Unconstrained Environments

Luiz A. Zanlorensi, Eduardo Luz, Rayson Laroca +3

The use of iris as a biometric trait is widely used because of its high level of distinction and uniqueness. Nowadays, one of the major research challenges relies on the recognitio…

cs.CV2018

Segmentation-Free Approaches for Handwritten Numeral String Recognition

Andre G Hochuli, Luiz E S Oliveira, Alceu S Britto +1

This paper presents segmentation-free strategies for the recognition of handwritten numeral strings of unknown length. A synthetic dataset of touching numeral strings of sizes 2-,…

cs.CV2018

Fixed-sized representation learning from Offline Handwritten Signatures of different sizes

Luiz G. Hafemann, Robert Sabourin, Luiz S. Oliveira

Methods for learning feature representations for Offline Handwritten Signature Verification have been successfully proposed in recent literature, using Deep Convolutional Neural Ne…

cs.CV2018

A Robust Real-Time Automatic License Plate Recognition Based on the YOLO Detector

Rayson Laroca, Evair Severo, Luiz A. Zanlorensi +4

Automatic License Plate Recognition (ALPR) has been a frequent topic of research due to many practical applications. However, many of the current solutions are still not robust in…