Automated COVID-19 diagnosis and classification using convolutional neural network with fusion based feature extraction model
Author:
Funder
Dept. of Edn. Govt. of India
Publisher
Springer Science and Business Media LLC
Subject
Cognitive Neuroscience
Link
https://link.springer.com/content/pdf/10.1007/s11571-021-09712-y.pdf
Reference32 articles.
1. Abbas A, Abdelsamea MM, Gaber MM (2020) Classification of COVID-19 in chest x-ray images using DeTraC deep convolutional neural network. Appl Intell 51:854–864
2. Apostolopoulos ID, Mpesiana TA (2020) Covid-19: automatic detection from X-ray images utilizing transfer learning with convolutional neural networks. Phys Eng Sci Med 43(2):635–640
3. Barstugan M, Ozkaya U, Ozturk S (2020) Coronavirus (COVID-19) classification using CT images by machine learning methods
4. Bejiga MB, Zeggada A, Nouffidj A, Melgani F (2017) A convolutional neural network approach for assisting avalanche search and rescue operations with UAV imagery. Remote Sens 9(2):100
5. Butt C, Gill J, Chun D, Babu BA (2020) Deep learning system to screen coronavirus disease 2019 pneumonia. Appl Intell 6:1–7
Cited by 21 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献
1. Chaotic Satin Bowerbird Optimizer Based Advanced AI Techniques for Detection of COVID-19 Diseases from CT Scans Images;New Generation Computing;2024-08-30
2. A Novel Hybrid Machine Learning-Based System Using Deep Learning Techniques and Meta-Heuristic Algorithms for Various Medical Datatypes Classification;Diagnostics;2024-07-09
3. A comprehensive health assessment approach using ensemble deep learning model for remote patient monitoring with IoT;Scientific Reports;2024-07-08
4. DETECTION AND CLASSIFICATION OF COVID-19 USING GRAY-LEVEL FEATURES AND ENSEMBLE CLASSIFIER;Biomedical Engineering: Applications, Basis and Communications;2024-06-28
5. Advancing COVID-19 poverty estimation with satellite imagery-based deep learning techniques: a systematic review;Spatial Information Research;2024-05-07
1.学者识别学者识别
2.学术分析学术分析
3.人才评估人才评估
"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370
www.globalauthorid.com
TOP
Copyright © 2019-2024 北京同舟云网络信息技术有限公司 京公网安备11010802033243号 京ICP备18003416号-3