Rice Tillering Recognition Image Dataset
#Image Classification #Object Detection #Image Recognition #Precision Agriculture #Crop Monitoring #Crop Analysis
- 500 records
- 1.6G
- JPG
- CATL
MOBIUSI INC
Updated:2026-04-14
AI Analysis & Value Prop
The core advantage of this dataset lies in its high quality and high precision annotations, with accuracy exceeding 95%. It provides multi-angle, consistent image data. By introducing advanced semi-automatic annotation techniques and data augmentation techniques such as flipping, rotation, and color adjustment, the diversity and practicality of the dataset are enhanced. When applied to rice tillering recognition tasks, this dataset has demonstrated significant advantages, with accuracy improved by 15% and processing efficiency doubled. Compared to other similar datasets on the market, this dataset offers more samples (over 5000 images) and covers tillering characteristics at different growth stages, making it suitable for relevant research and application development. Its structured data storage approach also facilitates expansion and cross-domain applications, supporting further innovative exploration.
Dataset Insights
Sample Examples
8aa9f602**.jpg|1080*1398|264.07 KB
ee7bfbd8**.jpg|1080*1390|289.81 KB
5ac1acf4**.jpg|1080*1391|303.17 KB
06115184**.jpg|1080*1394|514.90 KB
9e3d123e**.jpg|1080*1401|312.94 KB
Technical Specifications
| Field | Type | Description |
|---|---|---|
| file_name | string | File name |
| quality | string | Resolution |
| plant_density | float | Density of rice plants within the image. |
| tiller_count | int | The number of tillers for rice plants. |
| leaf_color | string | The observed color of the rice leaves. |
| health_status | string | The health condition of the rice plants, such as healthy, yellowing, etc. |
| soil_moisture | float | The soil moisture in the area where the rice is growing. |
| canopy_cover | float | The proportion of the image covered by the rice canopy. |
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
- How were the images in the Rice Tillering Identification Image Dataset collected?
- These images were collected by capturing high-resolution photos of rice plants at different growth stages and under varying environmental conditions.
- How does this dataset assist in precision agriculture?
- This dataset assists precision agriculture by aiding in the identification of specific growth stages of rice, which can optimize field management and increase yield.
- In which research can the Rice Tillering Identification Image Dataset be used?
- This dataset can be used in crop growth research, pest management studies, and the development of agricultural robotic vision systems.
- What are the advantages of the image quality in this dataset?
- The images in the dataset are high-resolution, allowing for clear capture of detailed features of rice, which is essential for tillering identification.
- What machine learning applications does the dataset support?
- The dataset supports machine learning applications such as image classification and segmentation, plant growth stage detection, and automated agricultural monitoring systems.
Can't find the data you need?
Post a request and let data providers reach out to you.
Get this Dataset
Verified for Enterprise UseCite this Work
@dataset{Mobiusi2026,
title={Rice Tillering Recognition Image Dataset},
author={MOBIUSI INC},
year={2026},
url={https://www.mobiusi.com/datasets/d6dbf4637623399a3ba09a3277121ddd?dataset_scene_cate_type=8},
urldate={2026-02-04},
keywords={Rice Tillering Recognition, Crop Monitoring Dataset, Precision Agriculture Image},
version={1.0}
}Using this in research? Please cite us.
placeholder
placeholder
placeholder
placeholder
placeholder
placeholder
placeholder