Latest Research in Automated Weed Control
29 research papers · 2026 median publication year
Top Research Topics in Automated Weed Control
- Smart Agriculture and AI — 18 papers
- Computer Vision and Pattern Recognition — 5 papers
- Remote Sensing in Agriculture — 2 papers
- Food composition and properties — 1 papers
- Species Distribution and Climate Change — 1 papers
- Insect Pheromone Research and Control — 1 papers
- Machine Learning — 1 papers
Highest-Cited Papers
- A comprehensive review of deep learning methods for weed classification in precision agriculture
- A Lightweight GDMM-YOLO11 Model for Cotton–Weed Instance Segmentation and Image-Plane Operation-Point Localization
- Machine Vision‐Based Morphological Benchmarking and Extrusion Optimization of Analog Rice: A Digital Image Analysis Framework for Agricultural Grain Quality Evaluation
- MCLC-NET: Multimodal Continual Learning for Leaf Counting
- YOLOv11-based real-time weed detection and autonomous precision spraying for hilly agriculture
- DeepPhenoTree-Apple Edition: a multi-site apple phenology RGB annotated dataset with deep learning baseline models
- Deep learning-based detection and counting of wheat seeds: Comparative benchmarking of YOLO models
- Deep learning-based classification of wet direct seeded rice, broadcasted direct seeded rice and transplanted rice using drone imagery for precision agriculture
- Field-based deep learning classification of cotton and weeds for machine-vision-assisted intra-row weed management
- BiFormer-Enhanced YOLOv11n for Accurate Maize Ear Detection in Seed Production Fields
- Comparative evaluation of classical machine learning and deep learning models for early weed detection in precision agriculture
- MHF-YOLO: An Improved YOLOv8n-Based Approach Developed for Commercial-Grade Honeysuckle Recognition
- Potato Planting Quality Detection and Reseeding System Based on Lightweight Detection and Multi-Frame Decision Making
- DropClick: Semi-Automated One-Click Segmentation for Agricultural Robotic Data
- Synthetic Imagery Improves Ecological Classification When Real Data Are Scarce, Not Direct Substitutes
- Device and Algorithm Co-Design for Precise Monitoring of Matsumurasca onukii Trap-Capture Dynamics in Field Environments
- PlantC2USeg: Cross-Scale Consistent Pre-Training for Few-Shot Unified Plant Point Cloud Segmentation
- An Optimized YOLO11n Model with Multi-Stage Attention Mechanisms for Pitaya Disease Detection
- A Lightweight Phenology-Aware YOLOv5 Framework for Tomato Growth Stage Detection in Resource-Constrained Bhutanese Greenhouse Environments
- Advances in Intelligent Detection Technologies for Litchi Diseases and Pests: From Fruit-Level Sensing to Orchard-Scale Monitoring
Sub-Regions
- Smart Agriculture and AI — 21 papers
- Computer Vision and Pattern Recognition — 11 papers
- Species Distribution and Climate Change — 9 papers
- Smart Agriculture and AI — 6 papers
- Insect Pheromone Research and Control — 2 papers
- Smart Agriculture and AI — 1 papers