Optimization of deep learning based segmentation method
Author:
Funder
Türkiye Bilimsel ve Teknolojik Araştirma Kurumu
Publisher
Springer Science and Business Media LLC
Subject
Geometry and Topology,Theoretical Computer Science,Software
Link
https://link.springer.com/content/pdf/10.1007/s00500-021-06711-3.pdf
Reference57 articles.
1. Akkus Z, Galimzianova A, Hoogi A, Rubin DL, Erickson BJ (2017) Deep learning for brain MRI segmentation: state of the art and future directions. J Digit Imaging 30:449–459
2. Albarqouni S, Baur C, Achilles F, Belagiannis V, Demirci S, Navab N (2016) Aggnet: deep learning from crowds for mitosis detection in breast cancer histology images. IEEE Trans Med Imaging 35:1313–1321
3. Anthimopoulos M, Christodoulidis S, Ebner L, Christe A, Mougiakakou S (2016) Lung pattern classification for interstitial lung diseases using a deep convolutional neural network. IEEE Trans Med Imaging 35:1207–1216
4. Bayramoglu N, Heikkilä J (2016) Transfer learning for cell nuclei classification in histopathology images. In: European conference on computer vision. Springer, pp 532–539
5. Bayramoglu N, Kannala J, Heikkilä J (2016) Deep learning for magnification independent breast cancer histopathology image classification. In: Pattern recognition (ICPR), 2016 23rd international conference on, 2016. IEEE, pp 2440–2445
Cited by 6 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. Development of hybrid models based on deep learning and optimized machine learning algorithms for brain tumor Multi-Classification;Expert Systems with Applications;2024-03
2. An Optimized Two Stage U-Net Approach for Segmentation of Pancreas and Pancreatic Tumor;2024
3. Multi-focus image fusion via online convolutional sparse coding;Multimedia Tools and Applications;2023-07-22
4. MULTIPLE CLASSIFICATION OF BRAIN TUMORS FOR EARLY DETECTION USING A NOVEL CONVOLUTIONAL NEURAL NETWORK MODEL;Eskişehir Osmangazi Üniversitesi Mühendislik ve Mimarlık Fakültesi Dergisi;2023-04-29
5. Classification of Scenes in Aerial Images with Deep Learning Models;Türk Doğa ve Fen Dergisi;2023-03-27
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