17 results for “Plant Disease Classification”

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Research ArticleOpen accessIn the abstractIdentification of the Presence of the "Swollen Shoot" Disease in Endemic Areas in Côte d'Ivoire Via Convolutional Neural NetworksCoulibaly Mamadou, Silue Kolo, Konan Hyacinthe Kouassi et al.The detection of Swollen Shoot disease and its control is one of the major objectives of research related to sustainable cocoa farming in Côte d'Ivoire. To contain the epidemic, the Cocoa Coffee Council (CCC) in collaboration with the National Agency for Support to Rural Development (ANADER) is responsible for prospecting and delimiting the infected areas as well as for uprooting … …American Journal of Engineering and Applied Sciences, Vol. 16, Issue 3 · 1 Oct 2023 · 6,064 accessesView PDF Cite

Research ArticleOpen accessIn the abstractA Backward Regressed Capsule Neural Network for Plant Leaf Disease DetectionJennifer Jepkoech, Benson Kipkemboi Kenduiywo, David Muchangi Mugo, Edna Chebet ToolThis study investigated the introduction ofbackward regression coupled with DenseNet features in a Capsule Neural Network(CapsNet) for plant leaf disease classification. Plant diseases are consideredone of the main factors influencing food production and therefore fast cropdisease detection and recognition are important in enhancing food securityinterventions. CapsNets have successfully been adopted for plant leaf diseaseclassification however, backpropagation of signals to preceding … …Journal of Computer Science, Vol. 18, Issue 9 · 8 Sep 2022 · 5,718 accessesView PDF Cite

Research ArticleOpen accessIn the abstractField Assessment of Anthracnose Disease Response for the Sorghum Germplasm Collection from the Mopti RegionJ. E. ErpeldingProblem statement: Sorghum anthracnose (Colletotrichum sublineolum) is a highly variable pathogen and new sources of host plant resistance are required for the development of resistant sorghum varieties. Germplasm collections are an important source of host plant resistance and screening germplasm will be essential to identify new sources of resistance. Approach: The sorghum (Sorghum bicolor) collection from the Mopti region of … …American Journal of Agricultural and Biological Sciences, Vol. 5, Issue 3 · 30 Sep 2010 · 8,213 accessesView PDF Cite

Research ArticleOpen accessAll words, across the recordAn Edge Efficient and Lightweight Hybrid CNN Vision Transformer Network With CBAM for IoT Based Plant Disease DetectionNyabeye Pangop Doris-Khöler, Kengni Ngangmo OlgaDetecting crop disease early enough to act on it remains a bottleneck for smallholder and precision farming alike, particularly when diagnosis depends on manual inspection or lab analysis that cannot keep pace with an outbreak. We present AgriViTNet, a compact CNN-Vision Transformer hybrid built for exactly this constraint: It extracts local texture cues through convolution, relates them across the whole … …Journal of Computer Science, Vol. 22, Issue 9 · 20 Sep 2026 · 578 accessesView PDF Cite

Research ArticleOpen accessAll words, across the recordAutomating Paddy Crop Disease Classification With Deep Learning ModelsShiva Shankar J, S. Palanivel, S. China VenkateswarluRice is a staple food crop for more than 10 countries. High consumption of rice demands better yield of crop. Timely disease diagnosis in paddy is fundamental to preventing yield losses and ensuring an adequate supply of rice for a rapidly rising worldwide population. Agriculture and modern farming is one of the fields where IoT and automation can have a … …Journal of Computer Science, Vol. 21, Issue 8 · 1 Sep 2025 · 5,696 accessesView PDF Cite

Research ArticleOpen accessAll words, across the recordExperimental Evaluation of Coffee Leaf Disease Classification and Recognition Based on Machine Learning and Deep Learning AlgorithmsKacoutchy Jean Ayikpa et al.Coffee plant diseases constitute a significant danger to world coffee production, and the greatest challenge is to detect these diseases as early as possible to save the crop. Traditional methods are most often based on visual observations, often with errors in diagnosing diseases. Machine Learning has become a tool that presents itself as an alternative for automatically identifying plant diseases. … …Journal of Computer Science, Vol. 18, Issue 12 · 10 Dec 2022 · 6,986 accessesView PDF Cite

Research ArticleOpen accessAll words, across the recordEarly Detection and Classification Approach for Plant Diseases based on MultiScale Image DecompositionAssia Ennouni, Noura Ouled Sihamman, My Abdelouahed Sabri, Abdellah AarabThis paper presents a new and powerful approach for detecting and classifying leaf diseases for plant diagnosis with high accuracy. The main contribution of this paper is that a hybrid approach is proposed by using the combination of Partial Differential Equations (PDE) based image decomposition, segmentation, feature extraction, features selection and classification aiming to improve the classification accuracy and provide … …Journal of Computer Science, Vol. 17, Issue 3 · 25 Mar 2021 · 7,205 accessesView PDF Cite