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관절 좌표 추정을 위한 다중 학습 방법
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| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | 이호경 | - |
| dc.contributor.author | 한정훈 | - |
| dc.contributor.author | 조용채 | - |
| dc.contributor.author | 문영식 | - |
| dc.date.accessioned | 2021-06-22T10:02:04Z | - |
| dc.date.available | 2021-06-22T10:02:04Z | - |
| dc.date.issued | 2019-06 | - |
| dc.identifier.uri | https://scholarworks.bwise.kr/erica/handle/2021.sw.erica/2872 | - |
| dc.description.abstract | In the field of human pose estimation, lack of dataset has always been a solid problem. Many research tried to overcome this issue by applying additional information such as depth information, body part segmentation, etc. In this paper, we focus on the effects of various information which are keypoint, silhouette and body part segmentation. By analyzing each cases, we propose an optimized network for human pose estimation. | - |
| dc.format.extent | 3 | - |
| dc.language | 한국어 | - |
| dc.language.iso | KOR | - |
| dc.publisher | 대한전자공학회 | - |
| dc.title | 관절 좌표 추정을 위한 다중 학습 방법 | - |
| dc.title.alternative | Multi-Stage learning for human pose estimation | - |
| dc.type | Article | - |
| dc.publisher.location | 대한민국 | - |
| dc.identifier.bibliographicCitation | 2019년 대한전자공학회 하계학술대회 논문집, pp 653 - 655 | - |
| dc.citation.title | 2019년 대한전자공학회 하계학술대회 논문집 | - |
| dc.citation.startPage | 653 | - |
| dc.citation.endPage | 655 | - |
| dc.description.isOpenAccess | N | - |
| dc.description.journalRegisteredClass | other | - |
| dc.identifier.url | https://www.dbpia.co.kr/journal/articleDetail?nodeId=NODE08761999 | - |
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