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Computer Vision Applications in Medical Diagnostics
作者: Pascal C. Weinberger
DOI:
10.1007/978-3-030-65896-0_11
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参考文章
(8)
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Yann Le Cun,
Learning Process in an Asymmetric Threshold Network
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,vol. 20, pp. 233- 240 ,(1986) ,
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2.
David E. Rumelhart, Geoffrey E. Hinton, Ronald J. Williams,
Learning representations by back-propagating errors
Nature.
,vol. 323, pp. 696- 699 ,(1988) ,
10.1038/323533A0
3.
Marvin Minsky,
Steps toward Artificial Intelligence
Proceedings of the IRE.
,vol. 49, pp. 8- 30 ,(1961) ,
10.1109/JRPROC.1961.287775
4.
Henning Müller, Antoine Rosset, Arnaud Garcia, Jean-Paul Vallée, Antoine Geissbuhler,
Informatics in radiology (infoRAD): benefits of content-based visual data access in radiology.
Radiographics.
,vol. 25, pp. 849- 858 ,(2005) ,
10.1148/RG.253045071
5.
Huazhu Fu, Yanwu Xu, Stephen Lin, Damon Wing Kee Wong, Jiang Liu,
DeepVessel: Retinal Vessel Segmentation via Deep Learning and Conditional Random Field
medical image computing and computer assisted intervention.
,vol. 9901, pp. 132- 139 ,(2016) ,
10.1007/978-3-319-46723-8_16
6.
Joachim Denzler, Christoph Käding, Clemens-Alexander Brust,
Active Learning for Deep Object Detection
arXiv: Computer Vision and Pattern Recognition.
,(2018)
7.
Rewa Sood, Binit Topiwala, Karthik Choutagunta, Rohit Sood, Mirabela Rusu,
An Application of Generative Adversarial Networks for Super Resolution Medical Imaging
international conference on machine learning and applications.
pp. 326- 331 ,(2018) ,
10.1109/ICMLA.2018.00055
8.
Navleen Kour, Sunanda, Sakshi Arora,
Computer-Vision Based Diagnosis of Parkinson’s Disease via Gait: A Survey
IEEE Access.
,vol. 7, pp. 156620- 156645 ,(2019) ,
10.1109/ACCESS.2019.2949744
来源期刊
Springer International Publishing
2021 年,
Volume: , Issue: ,
Page: 123-131
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