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ID-MSNet: An Enhanced Multi-Scale Network with Convolutional Attention for Pixel-Level Steel Defect Segmentation.

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Title: ID-MSNet: An Enhanced Multi-Scale Network with Convolutional Attention for Pixel-Level Steel Defect Segmentation.
Authors: Saberironaghi, Mohammadreza1 (AUTHOR), Ren, Jing1 (AUTHOR), Saberironaghi, Alireza1 (AUTHOR) alireza.saberironaghi@ontariotechu.ca
Source: Algorithms. Apr2026, Vol. 19 Issue 4, p294. 20p.
Database: Academic Search Ultimate
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  Data: ID-MSNet: An Enhanced Multi-Scale Network with Convolutional Attention for Pixel-Level Steel Defect Segmentation.
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  Data: <searchLink fieldCode="AR" term="%22Saberironaghi%2C+Mohammadreza%22">Saberironaghi, Mohammadreza</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Ren%2C+Jing%22">Ren, Jing</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Saberironaghi%2C+Alireza%22">Saberironaghi, Alireza</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> alireza.saberironaghi@ontariotechu.ca</i>
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  Data: <searchLink fieldCode="JN" term="%22Algorithms%22">Algorithms</searchLink>. Apr2026, Vol. 19 Issue 4, p294. 20p.
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=asn&AN=193433770
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        Value: 10.3390/a19040294
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      – Code: eng
        Text: English
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        StartPage: 294
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      – TitleFull: ID-MSNet: An Enhanced Multi-Scale Network with Convolutional Attention for Pixel-Level Steel Defect Segmentation.
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            NameFull: Ren, Jing
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              Text: Apr2026
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              Y: 2026
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