4 articles for “Agricultural Crop Disease Detection”

Set a search alert

Research ArticleOpen accessPhrase in the titleAgricultural Crop Disease Detection Using Convolutional Neural NetworksAtsu Alagah Komlavi, Harouna Naroua, Chaibou KadriMitigating food insecurity in Niger is of paramount importance. According to some researchers, agricultural yield is declining. The permanent annual food shortage was estimated to be between 25 and 50%. Loss of cereal agricultural production is caused by pests and plant diseases. Knowing that ordinary techniques became inefficient. Automatic detection of plant diseases using artificial intelligence becomes the best solution. … …Journal of Computer Science, Vol. 21, Issue 3 · 24 Jan 2025 · 7,547 accessesView PDF Cite

Research ArticleOpen accessIn the abstractImplementation and Performance Evaluation of YOLOv8 for Wheat Fungal Disease DetectionShivani Sood, Shallu Duggal, Monika Sethi et al.Among the many difficulties in producing wheat, a vital food source for the world, there are biotic variables like fungal diseases, which drastically lower crop output. Around the world, biotrophic fungi particularly, leaf rust, powdery mildew, and yellow rusts-have become a constant threat to wheat production. Traditional methods of identification and mitigation are labor-intensive, slow, and imprecise, limiting therefore early … …Journal of Computer Science, Vol. 22, Issue 4 · 2 May 2026 · 1,599 accessesView PDF Cite

Research ArticleOpen accessIn the abstractInternet of Things and Human Neocortex Inspired Algorithms for the Plant Disease Prediction-Sheath Blight for Paddy PlantThangaraj Ethilu, K. Parthiban, Arockia Jayadhas S et al.Sheath blight disease (Rhizoctonia solani) poses a critical threat to paddy (Oryza sativa) production, causing up to 50% yield losses under conducive environmental conditions. Existing computer vision-based disease detection systems identify infections only after symptom manifestation, while conventional machine learning prediction models suffer from high computational demands, data preprocessing requirements, and noise sensitivity. This research proposes a novel Hierarchical Temporal … …Journal of Computer Science, Vol. 21, Issue 11 · 18 Dec 2025 · 1,772 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