Latest Research in Smart Agriculture and AI
21 research papers · 2026 median publication year
Top Research Topics in Smart Agriculture and AI
- Smart Agriculture and AI — 12 papers
- Computer Vision and Pattern Recognition — 5 papers
- Remote Sensing in Agriculture — 2 papers
- Plant Surface Properties and Treatments — 1 papers
- Cell Image Analysis Techniques — 1 papers
Highest-Cited Papers
- UAV-based YOLOv11 system for automated detection and counting of male hemp plants bearing staminate flowers
- Deep learning-based classification of wet direct seeded rice, broadcasted direct seeded rice and transplanted rice using drone imagery for precision agriculture
- RQ-PointNeXt: An End-to-End 3D Point Cloud Instance Segmentation Method for Field Cotton Boll Phenotyping
- EgoMaize: A First-Person Maize Instance Segmentation Benchmark under Severe Field Occlusion
- Lightweight Detection of Blueberries at Different Maturity Stages in Complex Orchard Environments
- Hybrid Multi-View Embedded Vision for Functional Quality Assessment of Cut Roses Using a Raspberry Pi
- Zero-Shot 3D Plant Organ Segmentation with SAM3 and Semantic NeRFs
- A Two-Stage Weed Stem Localization Method Based on Crop Region Exclusion in Maize Seedling Fields
- WLP-YOLO: Edge-efficient UAV-based walnut detection for orchard monitoring via lightweight YOLOv8 and structured pruning
- Potato Planting Quality Detection and Reseeding System Based on Lightweight Detection and Multi-Frame Decision Making
- A dynamic multi-scale feature fusion and hierarchical attention network for leaf segmentation
- DropClick: Semi-Automated One-Click Segmentation for Agricultural Robotic Data
- RDA-YOLOv8n: A Directionally Refined and Structurally Optimized Approach for Tomato Maturity Detection
- DualSlim-YOLO: A Lightweight Detection Model Based on Unmanned Aerial Vehicle Imagery for Cauliflower Seedling Identification and Growth Assessment
- AGRICAM: A Track-Mounted Crop Pollination Monitoring Robot
- Advances in Intelligent Detection Technologies for Litchi Diseases and Pests: From Fruit-Level Sensing to Orchard-Scale Monitoring
- Towards Intelligent: A Robust Attention-Enhanced YOLO Framework for Oudemansiella raphanipes Detection in Factory Cultivation Systems
- Segmentation of Mandarin Oranges With Deep Learning for Postharvest Quality Analysis
- CMAE-Unet: A Study on a U-Net-Based Model for Semantic Segmentation of Unripe Tomato Images
- The Lettuce Nutritional Diagnosis Model of ResNet Improved by Integrating the MSA Mechanism