Corn Leaf Disease Recognition Dataset

#object detection #classification #agricultural disease detection #crop health monitoring

5000 records
1.2G
JPG/PNG/JSON
CATL
MOBIUSI INC

Updated:2026-04-16

AI Analysis & Value Prop

Current agriculture faces challenges of low disease detection efficiency and low recognition accuracy. Traditional manual detection methods are time-consuming, labor-intensive, and prone to errors. Existing automated detection solutions often rely on small-scale datasets, making it difficult to adapt to diverse disease manifestations. This dataset aims to provide a comprehensive corn leaf disease recognition dataset to support the training and evaluation of object detection algorithms. The dataset includes annotated images of various common diseases, aiming to improve the accuracy and efficiency of agricultural disease recognition. Data collection uses high-resolution cameras under natural light conditions to ensure image quality. To ensure data quality, multiple rounds of annotation and expert review processes are adopted to ensure annotation consistency and accuracy. Data is stored in JPEG format and organized using standard folder structures for easy subsequent use and management.

Dataset Insights

Sample Examples

0659984a**.jpg|6000*4000|4.51 MB

Technical Specifications

Field	Type	Description
file_name	string	File name
quality	string	Resolution
disease_type	string	Indicates the specific type of disease on the corn leaf.
disease_severity	string	Describes the severity of the disease on the corn leaf, such as mild, moderate, or severe.
leaf_area	float	The total area of the corn leaf (calculated based on image pixels).
infection_area	float	The infected area on the leaf due to disease (calculated based on image pixels).

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 agricultural use cases can this dataset be applied to?: This corn leaf disease detection dataset can be used for developing precision agriculture systems, assisting farmers in timely disease identification to optimize crop yields and reduce the use of chemicals.

What corn diseases are detected in this dataset?: The dataset covers various corn leaf diseases, such as rust, gray leaf spot, and leaf blight.

How to improve the model's detection accuracy on this dataset?: Model detection accuracy can be improved by data augmentation, using advanced object detection models, and tuning training parameters.

What is the data modality of this dataset and its characteristics?: The data modality of this dataset is images, featuring high resolution and diverse disease types, suitable for training deep learning models.

What are the technical challenges of using this dataset for object detection?: Technical challenges include complex backgrounds, highly similar disease features, and lighting variations under different shooting conditions.

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Cite this Work

@dataset{Mobiusi2025,
  title={Corn Leaf Disease Recognition Dataset},
  author={MOBIUSI INC},
  year={2025},
  url={https://www.mobiusi.com/datasets/8698447c0a632d112eaa558ad770a7ab?cate=2},
  urldate={2025-10-22},
  keywords={corn disease recognition, agricultural dataset, object detection dataset, crop disease detection},
  version={1.0}
}

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