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September 23, 2025AgriEngineeringOpen Access

YOLOv7 for Weed Detection in Cotton Fields Using UAV Imagery

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Analysis reveals YOLOv7 enhances weed detection accuracy in cotton fields, indicating improvements in precision agriculture.

YOLOv7 achieved the highest accuracy at 83%, improving weed detection in cluttered environments.
The study evaluated three YOLOv7 models, utilizing a dataset of 9249 images for effective weed and crop classification.
Fine-tuning of hyperparameters enhanced model performance, crucial for accurate detection in complex field conditions.
The UAV-based approach supports efficient weed management, minimizing herbicide use and promoting sustainable practices.

Das et al. (2025) studied this question.

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