Solon Alves Peixoto

Orcid: 0000-0002-3864-2506

According to our database1, Solon Alves Peixoto authored at least 13 papers between 2017 and 2022.

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

Timeline

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Bibliography

2022
Floor of log: a novel intelligent algorithm for 3D lung segmentation in computer tomography images.
Multim. Syst., 2022

Fully Automatic LPR Method Using Haar Cascade for Real Mercosur License Plates.
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

2021
Level set approach based on Parzen Window and floor of log for edge computing object segmentation in digital images.
Appl. Soft Comput., 2021

2020
Automatic classification of pulmonary diseases using a structural co-occurrence matrix.
Neural Comput. Appl., 2020

A high-efficiency energy and storage approach for IoT applications of facial recognition.
Image Vis. Comput., 2020

Cascaded Volumetric Fully Convolutional Networks for Whole-Heart and Great Vessel 3D segmentation.
Future Gener. Comput. Syst., 2020

Heart Arrhythmia Classification Based on Statistical Moments and Structural Co-occurrence.
Circuits Syst. Signal Process., 2020

Fast fully automatic heart fat segmentation in computed tomography datasets.
Comput. Medical Imaging Graph., 2020

2019
Automatic skin lesions segmentation based on a new morphological approach via geodesic active contour.
Cogn. Syst. Res., 2019

2018
Automatic histologically-closer classification of skin lesions.
Comput. Medical Imaging Graph., 2018

Neurologist-level classification of stroke using a Structural Co-Occurrence Matrix based on the frequency domain.
Comput. Electr. Eng., 2018

Lung Nodule Classification via Deep Transfer Learning in CT Lung Images.
Proceedings of the 31st IEEE International Symposium on Computer-Based Medical Systems, 2018

2017
A New Approach to Segment Hemorrhagic Stroke in Computed Tomography via Optimum Path Snakes.
Proceedings of the 16th IEEE International Conference on Machine Learning and Applications, 2017


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