Corn Seedling Recognition Dataset

#object detection #image classification #agricultural monitoring #crop health assessment #precision agriculture

20000 records
1.5G
JPG/PNG/JSON
CC-BY-NC-SA 4.0
MOBIUSI INC

Updated:2026-02-04

AI Analysis & Value Prop

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.

Dataset Insights

Sample Examples

9e22b0c9**.jpg|6000*4000|4.51 MB

Technical Specifications

Field	Type	Description
file_name	string	File name
quality	string	Resolution
plant_count	int	The number of corn seedlings present in the image.
average_plant_height	float	The average height of the corn seedlings in the image, measured in centimeters.
plant_health	string	The health status of each seedling marked as healthy, water deficient, pest/disease affected, etc.
soil_condition	string	The visible condition of the soil, such as moist, dry, weed-covered, etc.
lighting_condition	string	The lighting condition at the time the image was taken, such as sunny, cloudy, artificial light, etc.
weed_presence	boolean	Indicates whether weeds are present in the image.
background_elements	string	Visible background elements in the image, such as stones, tools, roads, etc.
plant_density	float	The density of plants in the image, expressed as the number of plants per square meter.

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

Frequently Asked Questions

What research fields can benefit from the Corn Seedling Recognition Dataset?: The Corn Seedling Recognition Dataset is suitable for applications in the agricultural research field, particularly in crop monitoring, smart agriculture, and pest control.

What type of image data does this dataset contain?: This dataset contains high-quality image data of corn seedlings for use in object detection tasks.

How can the Corn Seedling Recognition Dataset be used in agricultural automation?: The Corn Seedling Recognition Dataset can be used to train machine learning models for accurate identification and classification of corn seedlings in agricultural automation, thus improving agricultural productivity.

What are the prospects of conducting research using the Corn Seedling Recognition Dataset?: Conducting research using the Corn Seedling Recognition Dataset can provide technical support for the development of smart and precision agriculture, helping to increase crop yield and detection efficiency, which has broad prospects.

How is the performance of the Corn Seedling Recognition Dataset evaluated in object detection tasks?: In object detection tasks, the performance of the Corn Seedling Recognition Dataset can be evaluated using metrics such as accuracy, recall, and F1 score.

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Cite this Work

@dataset{Mobiusi2025,
  title={Corn Seedling Recognition Dataset},
  author={MOBIUSI INC},
  year={2025},
  url={https://www.mobiusi.com/datasets/ce8dff13815140e7a668e4a28e8faf02?cate=2},
  urldate={2025-10-23},
  keywords={corn seedling recognition, agricultural dataset, object detection, precision agriculture},
  version={1.0}
}

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