227 citations · 313 across the 17 of their papers we have counts for
8 papers · 1 filter
A Comparative Evaluation of Pre-trained Convolutional Neural Networks for Melanoma Detection
Wagner Moreno Schmitz, Marco Antonio de Castro Barbosa, Thiago Magalhães Amaral +2
Early diagnosis of melanoma is critical for improving patient survival rates. However, accurately distinguishing melanoma from other skin lesions remains a significant clinical cha…
Iterative Framework For Data Augmentation Of Segmented Fingerprints
João Leonardo H. D. Agnol, Wesley Augusto de Bona, Erick Oliveira Rodrigues +4
Infant biometrics presents unique challenges due to the physiological differences between infants and adults, compounded by the scarcity of available data for research that limits…
Recursive Class Connectivity Classification (R3C) Applied to Binary Image Segmentation for Improved Infant Fingerprint Enhancement
Joao Leonardo Harres Dall Agnol, Luiz Fernando Puttow Southier, Jefferson Tales 0liva +5
Image enhancement plays a crucial role in infant fingerprint matching, as child-specific characteristics such as smaller finger dimensions and thinner ridge structures often degrad…
X-Ray cardiac angiographic vessel segmentation based on pixel classification using machine learning and region growing
E O Rodrigues, L O Rodrigues, J J Lima +6
This work proposes a pixel-classification approach for vessel segmentation in x-ray angiograms. The proposal uses textural features such as anisotropic diffusion, features based on…
Cardiac fat segmentation using computed tomography and an image-to-image conditional generative adversarial neural network
Guilherme Santos da Silva, Dalcimar Casanova, Jefferson Tales Oliva +1
In recent years, research has highlighted the association between increased adipose tissue surrounding the human heart and elevated susceptibility to cardiovascular diseases such a…
An on-production high-resolution longitudinal neonatal fingerprint database in Brazil
Luiz F. P. Southier, Marcelo Filipak, Luiz A. Zanlorensi +5
The neonatal period is critical for survival, requiring accurate and early identification to enable timely interventions such as vaccinations, HIV treatment, and nutrition programs…
CondenseNeXt: An Ultra-Efficient Deep Neural Network for Embedded Systems
Priyank Kalgaonkar, Mohamed El-Sharkawy
Due to the advent of modern embedded systems and mobile devices with constrained resources, there is a great demand for incredibly efficient deep neural networks for machine learni…
Deep Learning Models for Visual Inspection on Automotive Assembling Line
Muriel Mazzetto, Marcelo Teixeira, Érick Oliveira Rodrigues +1
Automotive manufacturing assembly tasks are built upon visual inspections such as scratch identification on machined surfaces, part identification and selection, etc, which guarant…