Super-resolution recurrent convolutional neural networks for learning with multi-resolution whole slide images-Reference-Cited by-同舟云学术

登录注册会员服务联系我们

Super-resolution recurrent convolutional neural networks for learning with multi-resolution whole slide images

Published:2019-12-13 Issue:12 Volume:24 Page:1
ISSN:1083-3668
Container-title:Journal of Biomedical Optics
language:
Short-container-title:J. Biomed. Opt.

Author:

Mukherjee Lopamudra¹,Bui Huu Dat¹,Keikhosravi Adib²,Loeffler Agnes³,Eliceiri Kevin W.²

Affiliation:

1. University of Wisconsin–Whitewater, Department of Computer Science, Whitewater, Wisconsin

2. University of Wisconsin–Madison, Department of Biomedical Engineering, Madison, Wisconsin

3. MetroHealth Medical Center, Department of Pathology, Cleveland, Ohio

Funder

National Institutes of Health

Publisher

SPIE-Intl Soc Optical Eng

Subject

Biomedical Engineering,Atomic and Molecular Physics, and Optics,Biomaterials,Electronic, Optical and Magnetic Materials

Reference75 articles.

1. Computer Vision – ECCV 2014

2. Image Super-Resolution Using Deep Convolutional Networks

3. Convolutional Sparse Coding for Image Super-Resolution

4. ImageNet: A large-scale hierarchical image database

5. 80 Million Tiny Images: A Large Data Set for Nonparametric Object and Scene Recognition

Cited by 15 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. Efficient artificial intelligence approaches for medical image processing in healthcare: comprehensive review, taxonomy, and analysis;Artificial Intelligence Review;2024-07-29

2. Revolutionizing Prostate Whole-Slide Image Super-Resolution: A Comparative Journey from Regression to Generative Adversarial Networks;Uro;2024-06-27

3. Super-Resolution Reconstruction of Cell Images Based on Generative Adversarial Networks;IEEE Access;2024

4. Pathological image super-resolution using mix-attention generative adversarial network;International Journal of Machine Learning and Cybernetics;2023-03-03

5. Single patch super-resolution of histopathology whole slide images: a comparative study;Journal of Medical Imaging;2023-01-31

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