An empirical evaluation of extreme learning machine uncertainty quantification for automated breast cancer detection
Author:
Publisher
Springer Science and Business Media LLC
Subject
Artificial Intelligence,Software
Link
https://link.springer.com/content/pdf/10.1007/s00521-023-08992-1.pdf
Reference63 articles.
1. Abdel-Nasser M, Melendez J, Moreno A, Omer OA, Puig D (2017) Breast tumor classification in ultrasound images using texture analysis and super-resolution methods. Eng Appl Artif Intell 59:84–92
2. Abdul Salam M (2015) FPA-ELM model for stock market prediction. Int J Adv Res Comput Sci Softw Engi 5:1050–1063
3. Ahmadi A, Davoudi S, Daliri MR (2019) Computer aided diagnosis system for multiple sclerosis disease based on phase to amplitude coupling in covert visual attention. Comput Methods Programs Biomed 169:9–18
4. Ban X, Liu R, Shen Q, Wang Y (2016) Weighted extreme learning machine for balance and optimization learning. In: 2016 4th International conference on cloud computing and intelligence systems (CCIS), pp 6–10
5. Barata JCA, Hussein MS (2012) The Moore-Penrose pseudoinverse: a tutorial review of the theory. Braz J Phys 42(1):146–165
Cited by 7 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. Discrete ripplet-II transform feature extraction and metaheuristic-optimized feature selection for enhanced glaucoma detection in fundus images using least square-support vector machine;Multimedia Tools and Applications;2024-09-10
2. TfELM: Extreme Learning Machines framework with Python and TensorFlow;SoftwareX;2024-09
3. A novel fusion framework of deep bottleneck residual convolutional neural network for breast cancer classification from mammogram images;Frontiers in Oncology;2024-02-22
4. A Mine Water Source Prediction Model Based on LIF Technology and BWO-ELM;Journal of Fluorescence;2024-01-25
5. Integrating Advanced Deep Learning Features with SVM for Pathological Brain Detection: A Novel Hybrid Approach;2023 IEEE 3rd International Conference on Applied Electromagnetics, Signal Processing, & Communication (AESPC);2023-11-24
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