Explainable deep learning model for automatic mulberry leaf disease classification.

Nahiduzzaman, Md; Chowdhury, Muhammad E H; Salam, Abdus; Nahid, Emama; Ahmed, Faruque; Al-Emadi, Nasser; Ayari, Mohamed Arselene; Khandakar, Amith; Haider, Julfikar

Nahiduzzaman, Md; Chowdhury, Muhammad E H; Salam, Abdus; Nahid, Emama; Ahmed, Faruque; Al-Emadi, Nasser; Ayari, Mohamed Arselene; Khandakar, Amith; Haider, Julfikar.

Afiliação

Nahiduzzaman M; Department of Electrical & Computer Engineering, Rajshahi University of Engineering & Technology, Rajshahi, Bangladesh.
Chowdhury MEH; Department of Electrical Engineering, Qatar University, Doha, Qatar.
Salam A; Department of Electrical Engineering, Qatar University, Doha, Qatar.
Nahid E; Department of Electrical & Computer Engineering, Rajshahi University of Engineering & Technology, Rajshahi, Bangladesh.
Ahmed F; Department of Electrical & Computer Engineering, Rajshahi University of Engineering & Technology, Rajshahi, Bangladesh.
Al-Emadi N; Bangladesh Sericulture Research and Training Institute, Rajshahi, Bangladesh.
Ayari MA; Department of Electrical Engineering, Qatar University, Doha, Qatar.
Khandakar A; Department of Civil and Environmental Engineering, Qatar University, Doha, Qatar.
Haider J; Technology Innovation and Engineering Education Unit, Qatar University, Doha, Qatar.

Front Plant Sci ; 14: 1175515, 2023.

Article em En | MEDLINE | ID: mdl-37794930

Palavras-chave

Shapley Additive Explanations (SHAP); depth wise separable convolution; explainable artificial intelligence (XAI); mulberry leaf; parallel convolution

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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Revista: Front Plant Sci Ano de publicação: 2023 Tipo de documento: Article

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