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PulmonU-Net: a semantic lung disease segmentation model leveraging the benefit of multiscale feature concatenation and leaky ReLU.

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Title: PulmonU-Net: a semantic lung disease segmentation model leveraging the benefit of multiscale feature concatenation and leaky ReLU.
Authors: Shyni, H. Mary1, E, Chitra1, chitrae@srmist.edu.in
Source: Automatika: Journal for Control, Measurement, Electronics, Computing & Communications; Apr2024, Vol. 65 Issue 2, p641-651, 11p
Database: Applied Science & Technology Source
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PubType: Academic Journal
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  Data: PulmonU-Net: a semantic lung disease segmentation model leveraging the benefit of multiscale feature concatenation and leaky ReLU.
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      – Type: doi
        Value: 10.1080/00051144.2024.2314918
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      – Code: eng
        Text: English
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        PageCount: 11
        StartPage: 641
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      – TitleFull: PulmonU-Net: a semantic lung disease segmentation model leveraging the benefit of multiscale feature concatenation and leaky ReLU.
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            NameFull: Shyni, H. Mary
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            – D: 01
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              Text: Apr2024
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              Y: 2024
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            – TitleFull: Automatika: Journal for Control, Measurement, Electronics, Computing & Communications
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