[WACV 2023] Information and scripts for the CropAndWeed Dataset
Weed Detection and Laser Elimination on Farmbot Genesis.
Deep Learning-based Early Weed Segmentation using Motion Blurred UAV Images of Sorghum Fields
Using YOLOv7 for crop and weed detection
A curated collection of 45 high-quality RGB image datasets for computer vision in agriculture. Features datasets for weed detection, disease identification, and crop monitoring, focusing on natural field scenes. Part of our GIL 2025 survey paper.
Lawn robot for spraying weeds
CoFly-WeedDB dataset: 201 aerial RGB images for weed detection.
Detecting weed plants in fields using Ai techniques.
Code repository for sandplain lupin detection paper. Deep learning model for segmentation of morphologically similar weed and crop species
This work explores the power of semi-supervised learning (SSL), which combines labeled and unlabeled data to im- prove weed detection accuracy. This study presents a novel pipeline integrating YOLO-based object detection, pseudo-labeling, and Graph Neural Networks (GNNs) for transductive learning.
Weed detection method with training datasets
METADATA-FARMER ASSISTANCE WEBAPP | AI & ML
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RecyclingRush β»οΈ: Towards Continuous Floating Invasive Plant Removal Using Unmanned Surface Vehicles and Computer Vision, IEEE Access 2024.
AI-powered weed detection system developed for smart agriculture.
An autonomous farming robot system designed for precision agriculture applications.
'CNN_Sorghum_Weed_Classifier' is an artificial intelligence (AI) based software that can differentiate a sorghum sampling image from its associated weeds images.
Smart WeedCider β AI-powered weed detection and removal system for smarter, sustainable farming. Detect weeds using AI and help farmers take timely action to protect crops and improve yield. ππ±
Crop and Weed Detection using Deep Learning and Computer Vision for Precision Agriculture.
Agricultural weed segmentation using YOLO, ERFNet, and DeepLabV3+ on the PhenoBench dataset. Includes TensorRT for edge inference.
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