CoolFace
Datasetpublic

Mobiusi/Manual-Weed-Removal-Behavior-Recognition-Dataset

Manual Weed Removal Behavior Recognition Dataset The current agricultural sector faces problems of low efficiency in weed removal and high labor costs. Traditional weed removal methods require a large amount of manpower, and existing smart weed removal technologies are still in the early stages, unable to effectively identify and handle different types of weeds. To address these issues, this dataset aims to provide a high-quality manual weed removal behavior recognition dataset… See the full description on the dataset page: https://huggingface.co/datasets/Mobiusi/Manual-Weed-Removal-Behavior-Recognition-Dataset.

sourceHugging Facecc-by-nc-sa-4.0updated 7mo agoView on Hugging Face
0likes51downloads
Dataset Card

Manual Weed Removal Behavior Recognition Dataset

The current agricultural sector faces problems of low efficiency in weed removal and high labor costs. Traditional weed removal methods require a large amount of manpower, and existing smart weed removal technologies are still in the early stages, unable to effectively identify and handle different types of weeds. To address these issues, this dataset aims to provide a high-quality manual weed removal behavior recognition dataset to assist researchers and engineers in developing more efficient smart agricultural solutions. High-resolution cameras are used for data collection in real agricultural environments, ensuring the representativeness of the collected images. To ensure data quality, multiple rounds of annotation and expert reviews were conducted to ensure the consistency and accuracy of the annotations. The data is stored in JPG format and organized in folders for easy processing and analysis.

Technical Specifications

FieldTypeDescription
file_namestringFile name
qualitystringResolution
weed_typestringIdentify and label the type of weeds present in the images.
weed_locationstringSpecify the location of weeds in the image, represented by coordinates.
crop_typestringIdentify and label the type of crops present in the images.
crophealthstatusstringAssess and label the health status of crops in the images.
weed_densityfloatCalculate and label the density of weeds in a single image.
lighting_conditionsstringDescribe the lighting conditions during image capture, such as sunny, cloudy, etc.
camera_anglestringRecord and label the camera angle used for taking the picture.
timeofdaystringLabel the specific time of day when the image was taken, such as morning or afternoon.

Compliance Statement

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

Source & Contact

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