Detection of Impurities in Wool Based on Improved YOlOV8

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dc.contributor.authorLiu, Yangen_US
dc.contributor.authorJi, Yatuen_US
dc.contributor.authorRen, Qing Dao Er Jien_US
dc.contributor.authorShi, Baoen_US
dc.contributor.authorZhuang, Xufeien_US
dc.contributor.authorYao, Miaomiaoen_US
dc.contributor.authorLi, Xiaomeien_US
dc.contributor.editorChaine, Raphaëlleen_US
dc.contributor.editorDeng, Zhigangen_US
dc.contributor.editorKim, Min H.en_US
dc.date.accessioned2023-10-09T07:42:55Z
dc.date.available2023-10-09T07:42:55Z
dc.date.issued2023
dc.description.abstractIn the current production process of wool products, the cleaning of wool raw materials has been realized in an automated way. However, detecting whether the washed and dried wool still contains excessive impurities still requires manual testing. This method greatly reduces production efficiency. To solve the problem of detecting wool impurities, we propose an improved model based on YOLOv8. Our work applied some techniques to solve the low resource model training problem, and incorporated a block for small object detection into the new neural network structure. The newly proposed model achieved an accuracy of 84.3% on the self built dataset and also achieved good results on the VisDrone2019 dataset.en_US
dc.description.sectionheadersPosters
dc.description.seriesinformationPacific Graphics Short Papers and Posters
dc.identifier.doi10.2312/pg.20231284
dc.identifier.isbn978-3-03868-234-9
dc.identifier.pages117-118
dc.identifier.pages2 pages
dc.identifier.urihttps://doi.org/10.2312/pg.20231284
dc.identifier.urihttps://diglib.eg.org:443/handle/10.2312/pg20231284
dc.publisherThe Eurographics Associationen_US
dc.rightsAttribution 4.0 International License
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.subjectCCS Concepts: Computing methodologies -> Computer graphics; Image manipulation; Image processing
dc.subjectComputing methodologies
dc.subjectComputer graphics
dc.subjectImage manipulation
dc.subjectImage processing
dc.titleDetection of Impurities in Wool Based on Improved YOlOV8en_US
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