Giovanni Lucca França da Silva

Orcid: 0000-0001-6370-939X

Affiliations:
  • Federal University of Maranhão, Brazil


According to our database1, Giovanni Lucca França da Silva authored at least 13 papers between 2017 and 2023.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
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Links

Online presence:

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Bibliography

2023
Heart segmentation in planning CT using 2.5D U-Net++ with attention gate.
Comput. methods Biomech. Biomed. Eng. Imaging Vis., May, 2023

2021
Segmentation and quantification of COVID-19 infections in CT using pulmonary vessels extraction and deep learning.
Multim. Tools Appl., 2021

Automatic method for classifying COVID-19 patients based on chest X-ray images, using deep features and PSO-optimized XGBoost.
Expert Syst. Appl., 2021

2020
Superpixel-based deep convolutional neural networks and active contour model for automatic prostate segmentation on 3D MRI scans.
Medical Biol. Eng. Comput., 2020

Deployment of a Machine Learning System for Predicting Lawsuits Against Power Companies: Lessons Learned from an Agile Testing Experience for Improving Software Quality.
Proceedings of the 19th Brazilian Symposium on Software Quality, 2020

Automatic Prostate Segmentation on 3D MRI Scans Using Convolutional Neural Networks with Residual Connections and Superpixels.
Proceedings of the 2020 International Conference on Systems, Signals and Image Processing, 2020

Taxonomic Indexes for Automatic Prostate Segmentation on 3D MRI Scans Using Superpixels and Probabilistic Atlas.
Proceedings of the 2020 International Conference on Systems, Signals and Image Processing, 2020

2019
An automatic method for lung segmentation and reconstruction in chest X-ray using deep neural networks.
Comput. Methods Programs Biomed., 2019

An ergonomic evaluation method using a mobile depth sensor and pose estimation.
Proceedings of the 25th Brazillian Symposium on Multimedia and the Web, 2019

Prediction of unregistered power consumption lawsuits and its correlated factors based on customer data using extreme gradient boosting model.
Proceedings of the 2019 IEEE International Conference on Systems, Man and Cybernetics, 2019

2018
Classification of malignant and benign lung nodules using taxonomic diversity index and phylogenetic distance.
Medical Biol. Eng. Comput., 2018

Convolutional neural network-based PSO for lung nodule false positive reduction on CT images.
Comput. Methods Programs Biomed., 2018

2017
Lung nodules diagnosis based on evolutionary convolutional neural network.
Multim. Tools Appl., 2017


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