Convolutional Neural Network Strategy for Skin Cancer Lesions Classifications and Detections

Abdala Nour, B. Boufama
{"title":"Convolutional Neural Network Strategy for Skin Cancer Lesions Classifications and Detections","authors":"Abdala Nour, B. Boufama","doi":"10.1145/3388440.3415988","DOIUrl":null,"url":null,"abstract":"Skin cancer is one of the most common forms of cancer that has widespread as a disease around the world. With early, accurate diagnosis, the chances of treating skin cancer are high. This has inspired us to design a deep learning model that uses a conventional neural network to automatically classify and detect different types of skin cancer images. Through this way the system takes actions to prevent and early detect skin cancer, leading to potentially the best approach for treatment. The goal of this research is to apply the systematic meta heuristic optimization and image detection techniques based on a convolutional neural network to efficiently and accurately detect and classify different types of skin lesions.","PeriodicalId":411338,"journal":{"name":"Proceedings of the 11th ACM International Conference on Bioinformatics, Computational Biology and Health Informatics","volume":"53 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-09-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 11th ACM International Conference on Bioinformatics, Computational Biology and Health Informatics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3388440.3415988","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3

Abstract

Skin cancer is one of the most common forms of cancer that has widespread as a disease around the world. With early, accurate diagnosis, the chances of treating skin cancer are high. This has inspired us to design a deep learning model that uses a conventional neural network to automatically classify and detect different types of skin cancer images. Through this way the system takes actions to prevent and early detect skin cancer, leading to potentially the best approach for treatment. The goal of this research is to apply the systematic meta heuristic optimization and image detection techniques based on a convolutional neural network to efficiently and accurately detect and classify different types of skin lesions.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
卷积神经网络在皮肤癌病灶分类与检测中的应用
皮肤癌是最常见的癌症之一,在世界范围内广泛传播。通过早期、准确的诊断,治疗皮肤癌的机会很高。这启发了我们设计一个深度学习模型,使用传统的神经网络来自动分类和检测不同类型的皮肤癌图像。通过这种方式,该系统采取措施预防和早期发现皮肤癌,从而找到潜在的最佳治疗方法。本研究的目的是应用基于卷积神经网络的系统元启发式优化和图像检测技术,高效准确地检测和分类不同类型的皮肤病变。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
RA2Vec CanMod From Interatomic Distances to Protein Tertiary Structures with a Deep Convolutional Neural Network Prediction of Large for Gestational Age Infants in Overweight and Obese Women at Approximately 20 Gestational Weeks Using Patient Information for the Prediction of Caregiver Burden in Amyotrophic Lateral Sclerosis
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1