Automated Breast Cancer Classification based on Modified Deep learning Convolutional Neural Network following Dual Segmentation

Author:

G Sajiv1,G Ramkumar1

Affiliation:

1. SIMATS,Saveetha School of Engineering,Chennai

Publisher

IEEE

Reference19 articles.

1. Comparison of Breast MRI Tumor Classification Using Human-Engineered Radiomics, Transfer Learning From Deep Convolutional Neural Networks, and Fusion Methods

2. Analysis of Mammogram Images using Active Contour Segmentation process and Level Set Method;megalan leo;International Journal of Emerging Technology and Advanced Engineering,0

3. An Ads-Csab Approach for Economic Denial of Sustainability Attacks in Cloud Storage;karthika;International Journal of Scientific & Technology Research,2020

4. Deep Learning-Based Hookworm Detection in Wireless Capsule Endoscopic Image Using AdaBoost Classifier

5. Simultaneous segmentation and classification of breast lesions from ultrasound images using Mask R-CNN

Cited by 45 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. Performance Evaluation of Deep Learning Based Industrial Safety Enhancement in Multiple Safety Equipment Detection;2024 International Conference on Advances in Computing, Communication and Applied Informatics (ACCAI);2024-05-09

2. A Comprehensive Analysis of Deep Learning Frameworks for Gastrointestinal Tract Image Segmentation;2024 International Conference on Advances in Computing, Communication and Applied Informatics (ACCAI);2024-05-09

3. Enhancing Accuracy in the Detection of Chondrosarcoma Using Mobile Net Algorithm and Comparison with Support Vector Machine;2024 Ninth International Conference on Science Technology Engineering and Mathematics (ICONSTEM);2024-04-04

4. AI-Enabled Data-Driven Approaches for Personalized Medicine and Healthcare Analytics;2024 Ninth International Conference on Science Technology Engineering and Mathematics (ICONSTEM);2024-04-04

5. Revolutionizing Deep Vein Thrombosis (DVT) Management: Machine Learning Unveils Precision in Early Detection;2024 Ninth International Conference on Science Technology Engineering and Mathematics (ICONSTEM);2024-04-04

同舟云学术

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