Datasets:
Tasks:
Object Detection
Modalities:
Text
Formats:
json
Languages:
English
Size:
< 1K
Tags:
object detection
image classification
agricultural monitoring
crop health assessment
precision agriculture
License:
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87a824d
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Parent(s):
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- README.md +60 -0
.gitattributes
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# Audio files - uncompressed
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README.md
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| 1 |
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---
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tags:
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- object detection
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- image classification
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- agricultural monitoring
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- crop health assessment
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- precision agriculture
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license: cc-by-nc-sa-4.0
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task_categories:
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- object-detection
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language:
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- en
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pretty_name: Corn Seedling Recognition Dataset
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size_categories:
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- 1B<n<10B
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---
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# Corn Seedling Recognition Dataset
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The current challenge in the agriculture industry is the precision and inefficiency of crop growth monitoring. Traditional methods often rely on manual observation, which is inefficient and prone to errors. Existing solutions mostly involve manual annotation, lacking standardization and consistency. This dataset aims to promote automated monitoring technology in the agricultural field by building a high-quality corn seedling recognition dataset. The dataset includes corn seedling images from different regions, captured using high-resolution cameras to ensure image clarity. During data collection, multiple rounds of annotation and expert review were adopted to ensure the quality of data labeling. The storage format is JPG, organized such that each image corresponds to an annotation file containing bounding boxes and category information.
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## Technical Specifications
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| Field | Type | Description |
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| :--- | :--- | :--- |
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| file_name | string | File name |
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| quality | string | Resolution |
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| plant_count | int | The number of corn seedlings present in the image. |
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| average_plant_height | float | The average height of the corn seedlings in the image, measured in centimeters. |
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| plant_health | string | The health status of each seedling marked as healthy, water deficient, pest/disease affected, etc. |
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| soil_condition | string | The visible condition of the soil, such as moist, dry, weed-covered, etc. |
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| lighting_condition | string | The lighting condition at the time the image was taken, such as sunny, cloudy, artificial light, etc. |
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| weed_presence | boolean | Indicates whether weeds are present in the image. |
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| background_elements | string | Visible background elements in the image, such as stones, tools, roads, etc. |
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| plant_density | float | The density of plants in the image, expressed as the number of plants per square meter. |
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## Compliance Statement
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<table>
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<tr>
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<td>Authorization Type</td>
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<td>CC-BY-NC-SA 4.0 (Attribution–NonCommercial–ShareAlike)</td>
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</tr>
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<tr>
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<td>Commercial Use</td>
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<td>Requires exclusive subscription or authorization contract (monthly or per-invocation charging)</td>
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</tr>
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<tr>
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<td>Privacy and Anonymization</td>
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<td>No PII, no real company names, simulated scenarios follow industry standards</td>
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</tr>
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<tr>
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<td>Compliance System</td>
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<td>Compliant with China's Data Security Law / EU GDPR / supports enterprise data access logs</td>
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</tr>
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</table>
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## Source & Contact
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If you need more dataset details, please visit [Mobiusi](https://www.mobiusi.com/datasets/ce8dff13815140e7a668e4a28e8faf02?utm_source=huggingface&utm_medium=referral). or contact us via contact@mobiusi.com
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