Malaria Disease Cell Classification With Highlighting Small Infected Regions
Author:
Affiliation:
1. Department of Computer Engineering, Kumoh National Institute of Technology, Seowon-gu, Gumi-si, South Korea
2. Department of Computer Science, Chungbuk National University, Seowon-gu, Cheongju-si, South Korea
Funder
Kumoh National Institute of Technology
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
General Engineering,General Materials Science,General Computer Science,Electrical and Electronic Engineering
Link
http://xplorestaging.ieee.org/ielx7/6287639/10005208/10044090.pdf?arnumber=10044090
Reference40 articles.
1. Machine learning approach for automated screening of malaria parasite using light microscopic images
2. Regularization for deep learning: A taxonomy;kuka?ka;ArXiv 1710 10686,2017
3. Automatic detection of Plasmodium parasites from microscopic blood images
4. A survey of transfer learning
5. Automatic System for Classification of Erythrocytes Infected with Malaria and Identification of Parasite's Life Stage
Cited by 5 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. Computer-Aided Diagnosis Systems for Automatic Malaria Parasite Detection and Classification: A Systematic Review;Electronics;2024-08-11
2. Deep learning-based blood cell classification from microscopic images for haematological disorder identification;Multimedia Tools and Applications;2024-08-01
3. Malaria Parasite Detection using 2D CNN;2024 International Conference on Inventive Computation Technologies (ICICT);2024-04-24
4. A Review on Computational Methods Based on Deep Learning and Transfer Learning Techniques for Malaria Detection;2024 10th International Conference on Automation, Robotics and Applications (ICARA);2024-02-22
5. Automatic classification of 10 blood cell subtypes using transfer learning via pre-trained convolutional neural networks;Informatics in Medicine Unlocked;2024
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