A novel multi-head CNN design to identify plant diseases using the fusion of RGB images

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dc.authoridKAYA, Yasin/0000-0002-9074-0189
dc.authoridGursoy, Ercan/0000-0001-6974-2705
dc.contributor.authorKaya, Yasin
dc.contributor.authorGursoy, Ercan
dc.date.accessioned2025-01-06T17:44:01Z
dc.date.available2025-01-06T17:44:01Z
dc.date.issued2023
dc.description.abstractPlant diseases and insect pests cause a significant threat to agricultural production. Early detection and diagnosis of these diseases are critical and can reduce economic losses. The recent development of deep learning (DL) benefits various fields, such as image processing, remote sensing, medical diagnosis, and agriculture. This work proposed a novel approach based on DL for plant disease detection by fusing RGB and segmented images. A multi-headed DenseNet-based architecture was developed, considering two images as input. We evaluated the model on a public dataset, PlantVillage, consisting of 54183 images with 38 classes. The fivefold cross-validation technique achieved an average accuracy, recall, precision, and f1-score of 98.17%, 98.17%, 98.16%, and 98.12%, respectively. The proposed approach can distinguish various plant diseases with different characteristics by image fusion. The high success rate with low standard deviation proves the robustness of the model, and the model can be integrated into plant disease detection and early warning system.
dc.identifier.doi10.1016/j.ecoinf.2023.101998
dc.identifier.issn1574-9541
dc.identifier.issn1878-0512
dc.identifier.scopus2-s2.0-85146953850
dc.identifier.scopusqualityQ1
dc.identifier.urihttps://doi.org/10.1016/j.ecoinf.2023.101998
dc.identifier.urihttps://hdl.handle.net/20.500.14669/2879
dc.identifier.volume75
dc.identifier.wosWOS:000926233600001
dc.identifier.wosqualityQ1
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.language.isoen
dc.publisherElsevier
dc.relation.ispartofEcological Informatics
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.snmzKA_20241211
dc.subjectPlant disease detection
dc.subjectFusion CNN
dc.subjectDeep learning
dc.subjectDenseNet
dc.titleA novel multi-head CNN design to identify plant diseases using the fusion of RGB images
dc.typeArticle

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