Color-Aware Two-Branch DCNN for Efficient Plant Disease Classification

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dc.contributor.authorSchwarz Schuler, Joao Paulo
dc.contributor.authorRomani, Santiago
dc.contributor.authorAbdel-Nasser, Mohamed
dc.contributor.authorRashwan, Hatem
dc.contributor.authorPuig, Domenec
dc.coverage.issue1cs
dc.coverage.volume28cs
dc.date.accessioned2022-06-30T07:01:57Z
dc.date.available2022-06-30T07:01:57Z
dc.date.issued2022-06-30cs
dc.description.abstractDeep convolutional neural networks (DCNNs) have been successfully applied to plant disease detection. Unlike most existing studies, we propose feeding a DCNN CIE Lab instead of RGB color coordinates. We modified an Inception V3 architecture to include one branch specific for achromatic data (L channel) and another branch specific for chromatic data (AB channels). This modification takes advantage of the decoupling of chromatic and achromatic information. Besides, splitting branches reduces the number of trainable parameters and computation load by up to 50% of the original figures using modified layers. We achieved a state-of-the-art classification accuracy of 99.48% on the Plant Village dataset and 76.91% on the Cropped-PlantDoc dataset.en
dc.formattextcs
dc.format.extent55-62cs
dc.format.mimetypeapplication/pdfen
dc.identifier.citationMendel. 2022 vol. 28, č. 2, s. 55-62. ISSN 1803-3814cs
dc.identifier.doi10.13164/mendel.2022.1.055en
dc.identifier.issn2571-3701
dc.identifier.issn1803-3814
dc.identifier.urihttp://hdl.handle.net/11012/208129
dc.language.isoencs
dc.publisherInstitute of Automation and Computer Science, Brno University of Technologycs
dc.relation.ispartofMendelcs
dc.relation.urihttps://mendel-journal.org/index.php/mendel/article/view/176cs
dc.rightsCreative Commons Attribution-NonCommercial-ShareAlike 4.0 International licenseen
dc.rights.accessopenAccessen
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/4.0en
dc.subjectCNNen
dc.subjectDCNNen
dc.subjectDeep Learningen
dc.subjectPlant Diseaseen
dc.subjectCIE LABen
dc.subjectNeural Networksen
dc.subjectArtificial Intelligenceen
dc.subjectMultipathen
dc.titleColor-Aware Two-Branch DCNN for Efficient Plant Disease Classificationen
dc.type.driverarticleen
dc.type.statusPeer-revieweden
dc.type.versionpublishedVersionen
eprints.affiliatedInstitution.facultyFakulta strojního inženýrstvícs
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