Search Results for author: Diego R. Lucio

Found 7 papers, 1 papers with code

On the Cross-dataset Generalization in License Plate Recognition

1 code implementation2 Jan 2022 Rayson Laroca, Everton V. Cardoso, Diego R. Lucio, Valter Estevam, David Menotti

Automatic License Plate Recognition (ALPR) systems have shown remarkable performance on license plates (LPs) from multiple regions due to advances in deep learning and the increasing availability of datasets.

Data Augmentation License Plate Detection +4

A New Periocular Dataset Collected by Mobile Devices in Unconstrained Scenarios

no code implementations24 Nov 2020 Luiz A. Zanlorensi, Rayson Laroca, Diego R. Lucio, Lucas R. Santos, Alceu S. Britto Jr., David Menotti

Thus, the use of datasets containing many subjects is essential to assess biometric systems' capacity to extract discriminating information from the periocular region.

Face Recognition Image Classification +1

CNN Hyperparameter tuning applied to Iris Liveness Detection

no code implementations12 Feb 2020 Gabriela Y. Kimura, Diego R. Lucio, Alceu S. Britto Jr., David Menotti

The iris pattern has significantly improved the biometric recognition field due to its high level of stability and uniqueness.

General Classification

Deep Representations for Cross-spectral Ocular Biometrics

no code implementations21 Nov 2019 Luiz A. Zanlorensi, Diego R. Lucio, Alceu S. Britto Jr., Hugo Proença, David Menotti

One of the major challenges in ocular biometrics is the cross-spectral scenario, i. e., how to match images acquired in different wavelengths (typically visible (VIS) against near-infrared (NIR)).

Face Recognition

Simultaneous Iris and Periocular Region Detection Using Coarse Annotations

no code implementations31 Jul 2019 Diego R. Lucio, Rayson Laroca, Luiz A. Zanlorensi, Gladston Moreira, David Menotti

In this work, we propose to detect the iris and periocular regions simultaneously using coarse annotations and two well-known object detectors: YOLOv2 and Faster R-CNN.

Iris Segmentation

Robust Iris Segmentation Based on Fully Convolutional Networks and Generative Adversarial Networks

no code implementations4 Sep 2018 Cides S. Bezerra, Rayson Laroca, Diego R. Lucio, Evair Severo, Lucas F. Oliveira, Alceu S. Britto Jr., David Menotti

In this paper, two approaches for robust iris segmentation based on Fully Convolutional Networks (FCNs) and Generative Adversarial Networks (GANs) are described.

Iris Segmentation Segmentation

Fully Convolutional Networks and Generative Adversarial Networks Applied to Sclera Segmentation

no code implementations22 Jun 2018 Diego R. Lucio, Rayson Laroca, Evair Severo, Alceu S. Britto Jr., David Menotti

The initial and paramount step for performing this type of recognition is the segmentation of the region of interest, i. e. the sclera.

Generative Adversarial Network

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