Mobiusi/Weed-Coverage-Identification-Dataset

Weed Coverage Identification Dataset

The main challenge facing agriculture today is the automatic identification and management of weeds. Traditional manual detection methods are inefficient and costly. Existing solutions often rely on human experience, with low accuracy and efficiency. Therefore, this dataset aims to promote the development of smart agriculture through high-quality weed coverage data, helping researchers and farmers use modern technology to improve farming efficiency. The dataset is collected using high-resolution cameras, capturing farmland images under different lighting and climate conditions. Multiple rounds of annotation and expert review ensure data accuracy and consistency. The data is stored in JPG format and organized by farmland area for easy use and management. The core advantage of this dataset is its high annotation accuracy, with all image annotations exceeding 95% accuracy, providing strong practical value. By introducing new data enhancement technologies, the model's target detection performance has improved by 15% compared to traditional algorithms, effectively improving weed management efficiency in practical applications.

Technical Specifications

Field	Type	Description
file_name	string	File name
quality	string	Resolution
weed_coverage_percentage	float	The percentage of the area covered by weeds relative to the total area in the image.
weed_types	string	A list of weed species identified in the image.

Compliance Statement

Authorization Type	CC-BY-NC-SA 4.0 (Attribution–NonCommercial–ShareAlike)
Commercial Use	Requires exclusive subscription or authorization contract (monthly or per-invocation charging)
Privacy and Anonymization	No PII, no real company names, simulated scenarios follow industry standards
Compliance System	Compliant with China's Data Security Law / EU GDPR / supports enterprise data access logs

Source & Contact

If you need more dataset details, please visit Mobiusi. or contact us via contact@mobiusi.com