期刊文献+

图像识别技术在医学领域的应用及商业模式探讨 被引量:4

下载PDF
导出
摘要 随着计算机技术的进步及消费者需求的提升,近年来,人工智能已逐渐成为社会各界热议及研究的对象。而基于深度学习的图像识别技术作为人工智能的重要研究领域,在研究中也受到学者的广泛关注。本文从人工智能的发展背景入手,对图像识别技术在医学领域的应用进行梳理,并对其商业模式进行探讨,并提出合理的对策和办法,以促进人工智能技术在医疗领域的落地及应用。
作者 罗诚 朱婷婷
机构地区 四川大学商学院
出处 《经贸实践》 2018年第9X期219-220,共2页 Economic Practice
  • 相关文献

参考文献1

二级参考文献40

  • 1AREL I,ROSE D C, KARNOWSKI T P. Deep machine learn- ing- A new frontier in artificial intelligence research [ J l- Computational intelligence magazine,2010,5(4) :13-18.
  • 2MARKOFF J. Scientists see promise in deep-learning pro- grams [ N ]. The New York Times, 2012-11-23.
  • 3PLIS S M , HJELM D R,SALAKHUTDINOV R,et al. Deep learning for neuroimaging: a validation study [ J ] Frontiers in neuroscience,2014( 8 ) :229.
  • 4ELFWING S, UCHIBE E, DOYA K. Expected energy-based restricted Boltzmann machine for classification [ J 1- Neural networks, 2015 ( 64 ) : 29 -38.
  • 5MOCANU D C, AMMAR H B. Factored four way conditional restricted Boltzmann machines for activity recognition [ J ]. Pattern recognition letters, 2015 (66) : 100-108.
  • 6LIU P,HAN S Z, MENG Z B,et al. Facial expression rec- ognition via a boosted deep belief network [ C ]//Proc. the 2014 IEEE Conference on Computer Vision and Pattern Recognition. [ S. 1. ] :IEEE ,2014 : 1805-1812.
  • 7HINTON G. Training products of experts by minimizing cont- rastive divergence [ J ]. Neural computation, 2006, 14 ( 8 ) : 1771-1800.
  • 8TIELEMAN T. Training restricted Boltzmann machines using approximations to the likelihood gradient [ C ]//Proc. the 25 th International Conference on Machine learning. [ S. 1. ] : IEEE,2008 : 1064-1071.
  • 9LOPES N, RIBEIRO B. Towards adaptive learning with im- proved convergence of deep belief networks on graphics pro- cessing units [ J ]1. Pattern recognition, 2014,47 ( 1 ) : 114- 127.
  • 10MANSANET J, ALBIOL A,PAREDES R,et al. Mask selec- tive regularization for restricted Bohzmann machines [ J ]. Neurocomputing, 2015,165 : 375-383.

共引文献14

同被引文献26

引证文献4

二级引证文献14

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部