Skin lesion classification in dermoscopic images using stacked Convolutional Neural Network
Author:
Funder
National Research Foundation of Korea
Publisher
Springer Science and Business Media LLC
Subject
General Computer Science
Link
https://link.springer.com/content/pdf/10.1007/s12652-021-03485-2.pdf
Reference60 articles.
1. Adegun A, Viriri S (2021) Deep learning techniques for skin lesion analysis and melanoma cancer detection: a survey of state-of-the-art. Artif Intell Rev 54:811–841
2. Akram T, Khan MA, Sharif M, Yasmin M (2018) Skin lesion segmentation and recognition using multichannel saliency estimation and m-svm on selected serially fused features. J Ambient Intell Human Comput. https://doi.org/10.1007/s12652-018-1051-5
3. Alexandrov LB, Kim J, Haradhvala NJ, Huang MN, Ng AWT, Wu Y, Boot A, Covington KR, Gordenin DA, Bergstrom EN et al (2020) The repertoire of mutational signatures in human cancer. Nature 578(7793):94–101
4. Ali ARA, Deserno TM (2012) A systematic review of automated melanoma detection in dermatoscopic images and its ground truth data. In: Medical Imaging 2012: Image Perception, Observer Performance, and Technology Assessment, International Society for Optics and Photonics, vol 8318, p 83181I
5. Argenziano G, Soyer HP (2001) Dermoscopy of pigmented skin lesions-a valuable tool for early. Lancet Oncol 2(7):443–449
Cited by 27 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. Enhanced skin cancer diagnosis using optimized CNN architecture and checkpoints for automated dermatological lesion classification;BMC Medical Imaging;2024-08-02
2. IoT based smart framework to predict air quality in congested traffic areas using SV-CNN ensemble and KNN imputation model;Computers and Electrical Engineering;2024-08
3. Systematic review of approaches to detection and classification of skin cancer using artificial intelligence: Development and prospects;Computers in Biology and Medicine;2024-08
4. Improving prediction of blood cancer using leukemia microarray gene data and Chi2 features with weighted convolutional neural network;Scientific Reports;2024-07-07
5. SKINC-NET: an efficient Lightweight Deep Learning Model for Multiclass skin lesion classification in dermoscopic images;Multimedia Tools and Applications;2024-06-04
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