Identification of Crop Diseases Using Deep Learning Algorithm
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https://doi.org/10.35219/mms.2022.3.04
Résumé
In this paper we present an algorithm based on deep learning. The program allows the user to select in a graphical interface the type of plant for which it is desired to insert images for disease identification. To train and test models, we used our own data set with a relatively small number of images, and all images were captured in culture, and not in laboratory conditions. The algorithm is based on deep learning approach.
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Références
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[11]. Fang T., Chen P., Zhang J., Wang B., Crop leaf disease grade identification based on an improved convolutional neural network, J Electron Imaging, 2020.
[2]. Amara J., Bouaziz B., Algergawy A., A deep learnin gbased approach for banana leaf diseases classification, (In) Proceedings of Datenbanksysteme für Business, Technologie und Web (BTW 2017) – Workshop Bonn: Gesellschaft für Informatik, 2017.
[3]. Arivazhagan S., Shebia R. N., Ananthi S., Varthini S. V., Detection of unhealthy region of plant leaves and classification of plant leaf diseases using texture features, Agricultural Engineering International: CIGR Journal 15, 2013.
[4]. Arivazhagan S., Ligi S. V., Mango Leaf Diseases Identification Using Convolutional Neural Network, International Journal of Pure and Applied Mathematics, 2018.
[5]. Atila M., Uar M., Akyol K., Uar E., Plant leaf disease classification using efficientnet deep learning model, Ecol Inform., 2021.
[6]. Sabrol H., Kumar S., Recent studies of image and soft computing techniques for plant disease recognition and classification, Int J Comput Appl., 2015.
[7]. Yalcin H., Razavi S., Plant classification using convolutional neural networks, In: 2016 5th international conference on agrogeoinformatics (agro-geoinformatics), New York: IEEE, 2016.
[8]. Fuentes A., Lee J., Lee Y., Yoon S., Park D. S., Anomaly detection of plant diseases and insects using convolutional neural networks, In: ELSEVIER conference ISEM 2017-The International Society for Ecological Modelling Global Conference, 2017.
[9]. Hasan M. J., Mahbub S., Alom M. S., Nasim M. A., Rice disease identification and classification by integrating support vector machine with deep convolutional neural network, In: 2019 1st International conference on advances in science, engineering and robotics technology (ICASERT), 2019.
[10]. Thenmozhi K., Reddy U. S., Crop pest classification based on deep convolutional neural network and transfer learning, Comput Electron Agric., 2019.
[11]. Fang T., Chen P., Zhang J., Wang B., Crop leaf disease grade identification based on an improved convolutional neural network, J Electron Imaging, 2020.
Publiée
2022-09-15
Comment citer
1.
MARIN F, MATACHE M, MARIN M, GURĂU C, GURĂU G. Identification of Crop Diseases Using Deep Learning Algorithm. The Annals of “Dunarea de Jos” University of Galati. Fascicle IX, Metallurgy and Materials Science [Internet]. 15sept.2022 [cité 25août2025];45(3):20-3. Available from: https://gup.ugal.ro/ugaljournals/index.php/mms/article/view/5499
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