Autor según el artículo: Schwarz Schuler JP; Romani S; Abdel-Nasser M; Rashwan H; Puig D
Departamento: Enginyeria Informàtica i Matemàtiques
Autor/es de la URV: Abdelnasser Mohamed Mahmoud, Mohamed / Puig Valls, Domènec Savi / Romaní Also, Santiago
Palabras clave: Plant village Plant leaf disease Deep learning Dcnn Computer vision Cnn Classification
Resumen: The Food and Agriculture Organization (FAO) estimated that plant diseases cost the world economy $220 billion in 2019. In this paper, we propose a lightweight Deep Convolutional Neural Network (DCNN) for automatic and reliable plant leaf diseases classification. The proposed method starts by converting input images of plant leaves from RGB to CIE LAB coordinates. Then, L and AB channels go into separate branches along with the first three layers of a modified Inception V3 architecture. This approach saves from 1/3 to 1/2 of the parameters in the separated branches. It also provides better classification reliability when perturbing the original RGB images with several types of noise (salt and pepper, blurring, motion blurring and occlusions). These types of noise simulate common image variability found in the natural environment. We hypothesize that the filters in the AB branch provide better resistance to these types of variability due to their relatively low frequency in the image-space domain.
Áreas temáticas: Medicina ii Interdisciplinar Información y documentación General o multidisciplinar Engenharias iv Engenharias iii Comunicació i informació Ciências agrárias i Artificial intelligence
Acceso a la licencia de uso: https://creativecommons.org/licenses/by/3.0/es/
Direcció de correo del autor: mohamed.abdelnasser@urv.cat santiago.romani@urv.cat domenec.puig@urv.cat
Identificador del autor: 0000-0002-1074-2441 0000-0001-6673-9615 0000-0002-0562-4205
Fecha de alta del registro: 2024-07-27
Versión del articulo depositado: info:eu-repo/semantics/publishedVersion
Enlace a la fuente original: https://www.researchgate.net/publication/355215213_Reliable_Deep_Learning_Plant_Leaf_Disease_Classification_Based_on_Light-Chroma_Separated_Branches
URL Documento de licencia: https://repositori.urv.cat/ca/proteccio-de-dades/
Referencia al articulo segun fuente origial: Frontiers In Artificial Intelligence And Applications. 339 375-382
Referencia de l'ítem segons les normes APA: Schwarz Schuler JP; Romani S; Abdel-Nasser M; Rashwan H; Puig D (2021). Reliable Deep Learning Plant Leaf Disease Classification Based on Light-Chroma Separated Branches. Amsterdam: IOS Press
DOI del artículo: 10.3233/FAIA210157
Entidad: Universitat Rovira i Virgili
Año de publicación de la revista: 2021
Tipo de publicación: Proceedings Paper
Repositori URV