DNN에서 효율적인 학습을 위한 활성화 함수에 대한 고찰
DC Field | Value | Language |
---|---|---|
dc.contributor.author | 조윤환 | - |
dc.contributor.author | 서영덕 | - |
dc.contributor.author | 박대준 | - |
dc.contributor.author | 정제창 | - |
dc.date.accessioned | 2021-07-30T05:33:45Z | - |
dc.date.available | 2021-07-30T05:33:45Z | - |
dc.date.created | 2021-05-14 | - |
dc.date.issued | 2016-11 | - |
dc.identifier.uri | https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/5468 | - |
dc.description.abstract | Deep learning is definitely notable in various classification field. DNN(Deep Neural Network) is a kind of algorithm for deep learning. It becomes important to choose a suitable activation function to make learn the various DNN structure. In this paper, we summarize the history of activation function playing a key role in DNN and propose an improvement direction for state of the art activation function. | - |
dc.language | 한국어 | - |
dc.language.iso | ko | - |
dc.publisher | 대한전자공학회 | - |
dc.title | DNN에서 효율적인 학습을 위한 활성화 함수에 대한 고찰 | - |
dc.type | Article | - |
dc.contributor.affiliatedAuthor | 정제창 | - |
dc.identifier.bibliographicCitation | 대한전자공학회 학술대회, pp.800 - 803 | - |
dc.relation.isPartOf | 대한전자공학회 학술대회 | - |
dc.citation.title | 대한전자공학회 학술대회 | - |
dc.citation.startPage | 800 | - |
dc.citation.endPage | 803 | - |
dc.type.rims | ART | - |
dc.type.docType | Proceeding | - |
dc.description.journalClass | 3 | - |
dc.description.isOpenAccess | N | - |
dc.description.journalRegisteredClass | other | - |
dc.identifier.url | https://www.dbpia.co.kr/journal/articleDetail?nodeId=NODE07071188 | - |
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