New perspectives on plant disease characterization based on deep learning

Lee Sue Han, Goeau Hervé, Bonnet Pierre, Joly Alexis. 2020. New perspectives on plant disease characterization based on deep learning. Computers and Electronics in Agriculture, 170:105220, 12 p.

https://doi.org/10.1016/j.compag.2020.105220

Article de revue ; Article de recherche ; Article de revue à facteur d'impact

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Quartile : Q1, Sujet : AGRICULTURE, MULTIDISCIPLINARY / Quartile : Q1, Sujet : COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Résumé : The control of plant diseases is a major challenge to ensure global food security and sustainable agriculture. Several recent studies have proposed to improve existing procedures for early detection of plant diseases through modern automatic image recognition systems based on deep learning. In this article, we study these methods in detail, especially those based on convolutional neural networks. We first examine whether it is more relevant to fine-tune a pre-trained model on a plant identification task rather than a general object recognition task. In particular, we show, through visualization techniques, that the characteristics learned differ according to the approach adopted and that they do not necessarily focus on the part affected by the disease. Therefore, we introduce a more intuitive method that considers diseases independently of crops, and we show that it is more effective than the classic crop-disease pair approach, especially when dealing with disease involving crops that are not illustrated in the training database. This finding therefore encourages future research to rethink the current de facto paradigm of crop disease categorization.

Mots-clés Agrovoc : maladie des plantes, analyse d'image, photo-interprétation

Mots-clés complémentaires : deep learning

Mots-clés libres : Plant diseases, Automated visual crops analysis, Deep Learning, Transfer learning

Classification Agris : H20 - Maladies des plantes
U30 - Méthodes de recherche

Champ stratégique Cirad : CTS 4 (2019-) - Santé des plantes, des animaux et des écosystèmes

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