412 0

Full metadata record

DC FieldValueLanguage
dc.contributor.author문영식-
dc.date.accessioned2020-01-15T06:27:44Z-
dc.date.available2020-01-15T06:27:44Z-
dc.date.issued2019-06-
dc.identifier.citation2019년도 대한전자공학회 하계종합학술대회 논문집, Page. 653 - 655en_US
dc.identifier.urihttp://www.dbpia.co.kr/journal/articleDetail?nodeId=NODE08761999&language=ko_KR-
dc.identifier.urihttps://repository.hanyang.ac.kr/handle/20.500.11754/121864-
dc.description.abstractIn 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.language.isoko_KRen_US
dc.publisher대한전자공학회en_US
dc.title관절 좌표 추정을 위한 다중 학습 방법en_US
dc.title.alternativeMulti-Stage learning for human pose estimationen_US
dc.typeArticleen_US
dc.relation.page1-3-
dc.contributor.googleauthor이호경-
dc.contributor.googleauthor한정훈-
dc.contributor.googleauthor조용채-
dc.contributor.googleauthor문영식-
dc.sector.campusE-
dc.sector.daehakCOLLEGE OF COMPUTING[E]-
dc.sector.departmentDIVISION OF COMPUTER SCIENCE-
dc.identifier.pidysmoon-
Appears in Collections:
COLLEGE OF COMPUTING[E](소프트웨어융합대학) > COMPUTER SCIENCE(소프트웨어학부) > Articles
Files in This Item:
There are no files associated with this item.
Export
RIS (EndNote)
XLS (Excel)
XML


qrcode

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.

BROWSE