Latest Research in Smart Agriculture and AI

Top Research Topics in Smart Agriculture and AI

• Smart Agriculture and AI — 94 papers
• Computer Vision and Pattern Recognition — 7 papers
• Remote Sensing in Agriculture — 3 papers
• Banana Cultivation and Research — 2 papers
• Fungal Plant Pathogen Control — 1 papers
• Powdery Mildew Fungal Diseases — 1 papers
• Traditional Chinese Medicine Studies — 1 papers
• Cell Image Analysis Techniques — 1 papers
• Robotics — 1 papers
• Spectroscopy and Chemometric Analyses — 1 papers

Highest-Cited Papers

1. Vision Meets Language: A RAG-Augmented YOLOv8 Framework for Coffee Disease Diagnosis and Farmer Assistance (1 citations)
2. Detection of Diseases in Maize Plants by Analyzing Foliar Images Using Machine Learning Techniques
3. <p>From Disease Recognition to Agronomic Action: Vision-Language Reinforcement Learning for Explainable Crop Monitoring Using PlantVillageVQA</p>
4. Multiscale sugarcane disease classification using EfficientNet transformer fusion
5. Deep learning-based application for automated leaf counting in medicinal orchid Dendrobium nobile L. using YOLOv5
6. Knowledge distillation-based image deblurring network for plant disease classification
7. RiceMamba-DETR: efficient rice disease detection via hybrid Mamba-transformer architecture with cross-scale feature aggregation and large-scale dataset
8. Evolution of apple scab prediction models from empirical systems to Artificial Intelligence based predictive frameworks
9. BFMambaNet: Boundary-Frequency-Guided Global Semantic Mamba Network for Fine-Grained Camellia oleifera Leaf Disease Segmentation
10. Quantifying Visual Symptom Severity in Plants Using Deep Learning: A Severity Scale Derived from Classification Model Outputs
11. SporaScan : cost‐effective, high‐precision leaf‐disc disease severity assessment for grapevine downy mildew
12. A controlled analysis of lightweight CNN variants for chilli leaf disease classification with class weighting, label smoothing and class imbalance handling
13. Cotton Leaf Disease Detection via Dual-Backbone CNN-Transformer Fusion with Quantitative XAI Comparison
14. iCorn: A Methodological Framework for Multi-Label Disease Classification in Maize Using Uncurated Field Images
15. Research on Wheat Drought Stress Recognition Based on Improved EfficientNet-B0
16. CT-PestNet: A novel crop pest classification model based on cross-scale feature distillation enhancement and vision transformer with local token interaction
17. iCorn: A Methodological Framework for Multi-Label Disease Classification in Maize Using Uncurated Field Images
18. Global-Local Feature-Based Rice Leaf Disease Classification Using Two-Stream Deep Neural Network Feature Fusion
19. LightTeaNet: A Weakly Supervised Lightweight CNN for Multi-Label Tea Leaf Disease Detection and Localization
20. AppleScab-LT: A Longitudinal Real-Field Apple Scab Dataset for Temporal Disease Progression Analysis