Luís Fabrício de F. Souza
Orcid: 0000-0002-3156-1359
According to our database1,
Luís Fabrício de F. Souza
authored at least 14 papers
between 2019 and 2023.
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Bibliography
2023
Divisible Cell-Segmentation: A New Approach for Stroke Detection and Segmentation in CT Scans Using Deep Learning and Fine-tuning.
Proceedings of the International Joint Conference on Neural Networks, 2023
New Health of Things Approach to Classification and Detection of Brain Tumors Using Transfer Learning for Segmentation in IMR Images.
Proceedings of the International Joint Conference on Neural Networks, 2023
2022
New fully automatic approach for tissue identification in histopathological examinations using transfer learning.
IET Image Process., 2022
New Approach in LPR Systems Using Deep Learning to Classify Mercosur License Plates with Perspective Adjustment.
Proceedings of the Intelligent Systems Design and Applications - 22nd International Conference on Intelligent Systems Design and Applications (ISDA 2022) Held December 12-14, 2022, 2022
Proceedings of the Intelligent Systems Design and Applications - 22nd International Conference on Intelligent Systems Design and Applications (ISDA 2022) Held December 12-14, 2022, 2022
Automatic Segmentation of Hemorrhagic Stroke on Brain CT Images Using Convolutional Neural Networks Through Fine-Tuning.
Proceedings of the International Joint Conference on Neural Networks, 2022
2021
A soft computing automatic based in deep learning with use of fine-tuning for pulmonary segmentation in computed tomography images.
Appl. Soft Comput., 2021
A Novel Web Platform for COVID-19 diagnosis using X-Ray exams and Deep Learning Techniques.
Proceedings of the International Joint Conference on Neural Networks, 2021
2020
Internet of Medical Things: An Effective and Fully Automatic IoT Approach Using Deep Learning and Fine-Tuning to Lung CT Segmentation.
Sensors, 2020
Automatic lung segmentation in CT images using mask R-CNN for mapping the feature extraction in supervised methods of machine learning using transfer learning.
Int. J. Hybrid Intell. Syst., 2020
An effective approach for CT lung segmentation using mask region-based convolutional neural networks.
Artif. Intell. Medicine, 2020
Internet of Medical Things - Based on Deep Learning Techniques for Segmentation of Lung and Stroke Regions in CT Scans.
IEEE Access, 2020
Intelligent Industrial IoT system for detection of short-circuit failure in windings of wind turbines.
Proceedings of the 2020 International Joint Conference on Neural Networks, 2020
2019
Automatic Lung Segmentation in CT Images Using Mask R-CNN for Mapping the Feature Extraction in Supervised Methods of Machine Learning.
Proceedings of the Intelligent Systems Design and Applications, 2019