Hybrid Convolutional Neural Network and Extreme Learning Machine for Kidney Stone Detection-Reference-Cited by-同舟云学术

登录注册会员服务联系我们

Hybrid Convolutional Neural Network and Extreme Learning Machine for Kidney Stone Detection

Published:2023-03-02 Issue: Volume: Page:
ISSN:
Container-title:2023 Second International Conference on Electronics and Renewable Systems (ICEARS)
language:
Short-container-title:

Author:

G Pandiya Rajan¹,Sapra Puneet²,Mary S. Suma Christal³,Chauhan Amit⁴,Parte Smita Athanere⁵,Nishant Neerav⁶

Affiliation:

1. KPR Institute of Engineering & Technology,Department of Computer Science and Engineering (AIML),Coimbatore,Tamilnadu,India

2. Rayat Bahara University,Computer Science and Engineering,Mohali,Punjab,India

3. Panimalar Engineering College,Department of Information Technology,Chennai,Tamilnadu,India

4. CHRIST (Deemed to be University),Department of Life Sciences,Bengaluru,Karnataka,India

5. MITS,Department of Computer Science and Engineering,Gwalior,Madhya Pradesh,India

6. Babu Banarasi Das University,School of Engineering,Department of Computer Science and Engineering,Lucknow,Uttar Pradesh,India

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10084918/10084923/10085243.pdf?arnumber=10085243

Reference25 articles.

1. MSS U-Net: 3D segmentation of kidneys and tumors from CT images with a multi-scale supervised U-Net

2. Comparison of bladder segmentation using deep-learning convolutional neural network with and without level sets;cha;Medical Imaging 2016 Computer-Aided Diagnosis,2016

3. Urinary Stone Detection on CT Images Using Deep Convolutional Neural Networks: Evaluation of Model Performance and Generalization

4. Kid-Net: Convolution Networks for Kidney Vessels Segmentation from CT-Volumes

5. Segmentation of kidneys using a new active shape model generation technique based on non-rigid image registration

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