SciTePress - Affiliation Profile

Research.Publish.Connect.

Title:
ISBN:
Year:
Acronym:
Subject:

Advanced Search Proceedings Search

If you're looking for an exact phrase use quotation marks on text fields.

Title:
Author:
Affiliation:
Subject:

Advanced Search Papers Search

If you're looking for an exact phrase use quotation marks on text fields.

Name:
Affiliation:
Country:
Conference:
Subject:

Advanced Search Authors Search

If you're looking for an exact phrase use quotation marks on text fields.

Name:
Country:
Subject:

Advanced Search Affiliations Search

If you're looking for an exact phrase use quotation marks on text fields.

Proceedings

Proceedings Search

Title:
ISBN:
Year:
Acronym:
Subject:

Advanced Search Proceedings Search

If you're looking for an exact phrase use quotation marks on text fields.

Papers

Papers Search

Title:
Author:
Affiliation:
Subject:

Advanced Search Papers Search

If you're looking for an exact phrase use quotation marks on text fields.

Authors

Authors Search

Name:
Affiliation:
Country:
Conference:
Subject:

Advanced Search Authors Search

If you're looking for an exact phrase use quotation marks on text fields.

Advanced Search

Affiliation

INESC-TEC Technology and Science, Campus da FEUP, Rua Dr. Roberto Frias 378, 4200 - 465 Porto, Portugal

Context (please use complete words only)

Field

Sort by

1 Papers

Classification of Images of Childhood Pneumonia using Convolutional Neural Networks

Topic: Medical Imaging and Diagnosis

Authors: A. A. Saraiva ¹ , N. M. Fonseca Ferreira ^{2

;

3

;

4} , Luciano Lopes de Sousa ⁵ , Nator Junior C. Junior C. Costa ⁵ , José Vigno Moura Sousa ^{5

;

6} , D. B. S. B. S. Santos ⁵ , Antonio Valente ^{2

;

7} and Salviano Soares ⁷

Affiliations: ¹ UTAD University, Coimbra, Portugal , ² INESC-TEC Technology and Science, Campus da FEUP, Rua Dr. Roberto Frias 378, 4200 - 465 Porto, Portugal , ³ Knowledge Engineering and Decision-Support Research Center (GECAD) of the Institute of Engineering, Polytechnic Institute of Porto, Portugal , ⁴ Department of Electrical Engineering, Institute of Engineering of Coimbra, Polytechnic Institute, Rua Pedro Nunes, 3031-601 Coimbra, Portugal , ⁵ State University of Piauí, Piauí, Brazil , ⁶ University Brazil, São Paulo, Brazil , ⁷ IEETA-UA and School of Science and Technology, University of Trás-os-Montes and Alto Douro, Vila Real, Portugal

Digital Object Identifier: 10.5220/0007404301120119

Proceedings of BIOIMAGING 2019/BIOSTEC, ISBN: 978-989-758-353-7

Quick Abstract

In this paper we describe a comparative classification of Pneumonia using Convolution Neural Network. The database used was the dataset Labeled Optical Coherence Tomography (OCT) and Chest X-Ray Images for Classification made available by (Kermany, 2018) with a total of 5863 images, with 2 classes: normal and pneumonia. To evaluate the generalization capacity of the models, cross-validation of k-fold was used. The classification models proved to be efficient compared to the work of (Kermany et al., 2018) which obtained 92.8 % and the present work had an average accuracy of 95.30 %.