Performance Analysis of Hyperparameters of Convolutional Neural Networks for COVID-19 X-ray Image Classification

被引：1

作者：

Hota, Sarbeswara ^{[1
]}

Satapathy, Pranati ^{[2
]}

Acharya, Biswa Mohan ^{[1
]}

机构：

[1] Siksha O Anusandhan, Dept Comp Applicat, Bhubaneswar, Odisha, India

[2] Utkal Univ, Dept IMCA, Bhubaneswar, Odisha, India

来源：

AMBIENT INTELLIGENCE IN HEALTH CARE, ICAIHC 2022 | 2023年 / 317卷

关键词：

D O I：

10.1007/978-981-19-6068-0_22

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Analysis of chest X-ray images of COVID infected patients is one of the important diagnostic strategies. The manual identification of these images may be erroneous and faulty. So the computer-aided diagnosis of COVID infections using deep learning techniques is becoming useful. In this paper, the classification of chest X-ray images using CNN is conducted, and the performance of different optimizers is studied. The dataset containing chest X-ray images of normal and COVID infected patients is collected from Kaggle. The experimental study suggested that Adam optimizer achieved 95.83% classification accuracy, and it outperformed the other three optimizers.

引用

页码：225 / 230

页数：6

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