Datasets:
tags:
- object detection
- behavior recognition
- agricultural monitoring
- smart agriculture
- precision agriculture
license: cc-by-nc-sa-4.0
task_categories:
- object-detection
language:
- en
pretty_name: Manual Weed Removal Behavior Recognition Dataset
size_categories:
- 1B<n<10B
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
| Field | Type | Description |
|---|---|---|
| file_name | string | File name |
| quality | string | Resolution |
| weed_type | string | Identify and label the type of weeds present in the images. |
| weed_location | string | Specify the location of weeds in the image, represented by coordinates. |
| crop_type | string | Identify and label the type of crops present in the images. |
| crop_health_status | string | Assess and label the health status of crops in the images. |
| weed_density | float | Calculate and label the density of weeds in a single image. |
| lighting_conditions | string | Describe the lighting conditions during image capture, such as sunny, cloudy, etc. |
| camera_angle | string | Record and label the camera angle used for taking the picture. |
| time_of_day | string | Label the specific time of day when the image was taken, such as morning or afternoon. |
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