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YOLOv8-MS-DWConv: enhancing hazardous goods detection in X-ray security imaging with multi-scale depthwise separable convolution.

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Title: YOLOv8-MS-DWConv: enhancing hazardous goods detection in X-ray security imaging with multi-scale depthwise separable convolution.
Authors: Diao, Qi1,2, diaoqi@graduate.utm.my, Chan, Weng Howe2, cwenghowe@utm.my, Zain, Azlan Mohd2, Chen, YiFan2,3
Source: PeerJ Computer Science; Feb2026, p1-37, 37p
Database: Applied Science & Technology Source
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  Availability: 0
Header DbId: aci
DbLabel: Applied Science & Technology Source
An: 192850776
AccessLevel: 2
PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 0
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  Data: YOLOv8-MS-DWConv: enhancing hazardous goods detection in X-ray security imaging with multi-scale depthwise separable convolution.
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PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=aci&AN=192850776
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      – Type: doi
        Value: 10.7717/peerj-cs.3593
    Languages:
      – Code: eng
        Text: English
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        PageCount: 37
        StartPage: 1
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      – TitleFull: YOLOv8-MS-DWConv: enhancing hazardous goods detection in X-ray security imaging with multi-scale depthwise separable convolution.
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            NameFull: Diao, Qi
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            NameFull: Chan, Weng Howe
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            NameFull: Zain, Azlan Mohd
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            NameFull: Chen, YiFan
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            – D: 01
              M: 02
              Text: Feb2026
              Type: published
              Y: 2026
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