비전/초분광 카메라와 AI 자율 인지형 기술을 이용한 스마트 수산식품 검사시스템
DC Field | Value | Language |
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dc.contributor.author | Kim, San | - |
dc.contributor.author | Kim, Ji-Hyun | - |
dc.contributor.author | Kim, Byung-Ki | - |
dc.contributor.author | Kim, Soo Mee | - |
dc.contributor.author | Park, Cho-Rong | - |
dc.date.accessioned | 2022-12-05T01:30:06Z | - |
dc.date.available | 2022-12-05T01:30:06Z | - |
dc.date.created | 2022-12-01 | - |
dc.date.issued | 2022-11-25 | - |
dc.identifier.uri | https://sciwatch.kiost.ac.kr/handle/2020.kiost/43523 | - |
dc.description.abstract | The current situation of the seafood processing industry is accelerating a serious labor force problem due to the avoidance of fishing villages and Growing age of the fishing village population. In addition, outdated facilities and inefficient processes reduce productivity competitiveness. In this study, Hyperspectral imaging(HSI) camera and vision cameras were used to develop and apply an intelligent autonomous cognitive smart process system to fill the labor force. It builds and automates the recognition process for defective products and foreign substances based on this. This can replace the existing inefficient production, inspection, and packaging procedures, solve the problem of labor, and can have positive effects on the future seafood market such as improvement of aquatic product quality, increase in productivity, and increase in export competitiveness. | - |
dc.description.uri | 2 | - |
dc.language | Korean | - |
dc.publisher | 한국동력기계학회 | - |
dc.relation.isPartOf | 2022년도 한국동력기계학회 추계학술대회 논문집 | - |
dc.title | 비전/초분광 카메라와 AI 자율 인지형 기술을 이용한 스마트 수산식품 검사시스템 | - |
dc.type | Conference | - |
dc.citation.conferenceDate | 2022-11-24 | - |
dc.citation.conferencePlace | KO | - |
dc.citation.conferencePlace | 아바니센트럴호텔 | - |
dc.citation.endPage | 171 | - |
dc.citation.startPage | 169 | - |
dc.citation.title | 2022년도 한국동력기계학회 추계학술대회 | - |
dc.contributor.alternativeName | 김수미 | - |
dc.identifier.bibliographicCitation | 2022년도 한국동력기계학회 추계학술대회, pp.169 - 171 | - |
dc.description.journalClass | 2 | - |