Seedling and Soil Segmentation Dataset
#Image Segmentation #Deep Learning Training #Crop Monitoring #Precision Agriculture #Soil Analysis
- 15000 records
- 2.8G
- JPG/PNG/JSON
- CATL
MOBIUSI INC
Updated:2026-04-13
AI Analysis & Value Prop
The current agricultural industry faces challenges such as low crop monitoring efficiency and inaccurate soil quality analysis. Existing solutions often rely on manual observation, which is inefficient and prone to errors. This dataset aims to address the issue of insufficient image segmentation accuracy by providing high-quality images of seedling and soil segmentation, supporting precision agriculture and intelligent crop management. The dataset contains 15,000 high-resolution images collected using high-performance cameras in various environments and lighting conditions, ensuring data diversity and representativeness. Quality control includes multiple rounds of annotation, annotation consistency checks, and expert reviews to ensure high data quality. The data is stored in JPG format, and mask data is organized in JSON format, facilitating subsequent deep learning training and analysis.
Dataset Insights
Sample Examples
26c37fc6**.jpg|3000*2000|1.43 MB
d068eee6**.jpg|2000*3000|773.02 KB
2a538fcb**.jpg|2000*3000|936.45 KB
d1184590**.jpg|5350*3567|3.21 MB
Technical Specifications
| Field | Type | Description |
|---|---|---|
| file_name | string | File name |
| quality | string | Resolution |
| soil_condition | string | The surface condition of the soil, such as dry or wet. |
| seedling_health | string | The health condition of the seedling, such as healthy or damaged. |
| lighting_condition | string | The lighting condition at the time of capturing the image, such as sunny or cloudy. |
Compliance Statement
| Authorization Type | Proprietary - Commercial AI Training License (No Redistribution) |
| 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 |
Frequently Asked Questions
- What is the importance of seedling and soil segmentation data?
- Seedling and soil segmentation data is crucial for precision agriculture, helping farmers and researchers to better monitor and manage crop growth environments.
- What specific agricultural applications can this dataset be used for?
- This dataset can be used for applications such as plant health monitoring, disease detection, automated irrigation systems, and soil quality assessment.
- How can this dataset be utilized to improve agricultural productivity?
- By analyzing and utilizing the seedling and soil segmentation data, agricultural producers can more efficiently use resources, apply fertilizers accurately, and optimize irrigation, thus increasing yield and reducing costs.
- What are some innovative use cases for this dataset in agricultural research?
- In agricultural research, this dataset can be used to develop new AI models for advanced crop monitoring and the development of automated agricultural machinery systems.
- What makes this dataset unique compared to other agricultural datasets?
- Unlike other agricultural datasets, the seedling and soil segmentation dataset focuses on semantic segmentation, which is particularly important for achieving finer geospatial crop monitoring.
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Verified for Enterprise UseCite this Work
@dataset{Mobiusi2025,
title={Seedling and Soil Segmentation Dataset},
author={MOBIUSI INC},
year={2025},
url={https://www.mobiusi.com/datasets/f3dfbb067954c9306f176361f8f487a3?cate=2},
urldate={2025-09-15},
keywords={Seedling Segmentation Dataset, Soil Segmentation, Agricultural Image Segmentation, Precision Agriculture Data},
version={1.0}
}Using this in research? Please cite us.
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