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논문 기본 정보
- 자료유형
- 학술저널
- 저자정보
- 발행연도
- 2020.1
- 수록면
- 117 - 126 (10page)
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초록· 키워드
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Recently, significant improvements have been made in artificial intelligence. The artificial neural network was introduced in the 1950s. However, because of the low computing power and insufficient datasets available at that time, artificial neural networks sufferedfrom overfitting and vanishing gradient problems for training deep networks. This concept has become more promising owing tothe enhanced big data processing capability, improvement in computing power with parallel processing units, and new algorithmsfor deep neural networks, which are becoming increasingly successful and attracting interest in many domains, including computervision, speech recognition, and natural language processing. Recent studies in this technology augur well for medical and healthcareapplications, especially in endoscopic imaging. This paper provides perspectives on the history, development, applications, andchallenges of deep-learning technology.
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등록된 정보가 없습니다.
참고문헌 (76)
참고문헌 신청
McCarthy J / 2006 / A proposal for the dartmouth summer research project on artificial intelligence, August 31, 1955 / AI Mag 27:12~14
Cortes C / 1995 / Support-vector networks / Mach Learn 20:273~297
Freund Y / 1997 / A decision-theoretic generalization of on-line learning and an application to boosting / J Comput Syst Sci 55:119~139
Perronnin F / 2010 / Improving the Fisher kernel for large-scale image classification / 11th European Conference on Computer Vision :143~156
Krizhevsky A / 2012 / ImageNet classification with deep convolutional neural networks / Advances in Neural Information Processing Systems(NIPS 2012) 25:1097~1105
Cortes C / 1995 / Support-vector networks / Mach Learn 20:273~297
Freund Y / 1997 / A decision-theoretic generalization of on-line learning and an application to boosting / J Comput Syst Sci 55:119~139
Perronnin F / 2010 / Improving the Fisher kernel for large-scale image classification / 11th European Conference on Computer Vision :143~156
Krizhevsky A / 2012 / ImageNet classification with deep convolutional neural networks / Advances in Neural Information Processing Systems(NIPS 2012) 25:1097~1105
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