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• W4385766937 abstract "ABSTRACTPlants are a major source of food all around the world, and they are mainly affected by diseases caused by pathogens, insects, and parasitic plants. If the diseases are identified in the earlier stage, then it will be easy to apply pesticides and prevent the disease from further propagation. To recognise these diseases at earlier stages automatically, different researchers have established artificial intelligence-based approaches using machine learning and deep learning approaches which can identify the diseased lesions with high accuracy. In this paper, a novel Hybrid Moth Flame Optimization Algorithm-butterfly optimisation algorithm (HMFO-BOA) based optimal ensemble deep transfer network (OEDTN) classifier for banana leaf disease identification is developed. The OEDTN architecture offers increased predictability for banana leaf disease using Maximum Mean Discrepancy (MMD), ensemble learning, domain adaptation, and parameter transfer learning. The feature extraction is done by constructing different Deep Transfer Networks (DTN) via diverse kernel MMD. Finally, the DTNs are integrated via ensemble learning to obtain the final classification outcomes. The MFOBOA algorithm assigns optimal voting weights for each DTN to dynamically construct the OEDTN architecture. In the consequent testing process, the input banana leaf disease images are categorised into diverse classes such as BBW (Banana Bacterial Wilt Disease), BBS (Banana Black Sigatoka Disease), Cordana, pestalotiopsis, Sigatoka, and healthy. The experiments conducted on the Banana Leaf and BBW-BBS datasets prove that the proposed model offers improved performance than the state-of-art techniques.KEYWORDS: Banana leaf disease predictionoptimal ensemble deep transfer networkmetaheuristic optimisationparameter transfer learning Disclosure statementNo potential conflict of interest was reported by the author(s).Human and animal rightsThis article does not contain any studies with human or animal subjects performed by any of the authors.Informed consentInformed consent was obtained from all individual participants included in the study.Data sharing is not applicable to this article as no new data were created or analysed in this study.Ethics approvalThis article does not contain any studies with human participants." @default.
• W4385766937 created "2023-08-12" @default.
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• W4385766937 date "2023-08-10" @default.
• W4385766937 modified "2023-09-28" @default.
• W4385766937 title "An efficient banana plant leaf disease classification using optimal ensemble deep transfer network" @default.
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• W4385766937 doi "https://doi.org/10.1080/0952813x.2023.2241867" @default.
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