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Mobiusi/Durian-Plantation-Disease-Leaf-Rot-Detection-Image-Dataset

Durian Plantation Disease Leaf Rot Detection Image Dataset Ensures high-quality data through multiple rounds of annotation and automated consistency checks, combined with reviews by agricultural pathology experts. The annotation team consists of 10 professionals in agriculture and computer vision. Pre-processing steps include noise reduction, size adjustments, and color normalization to enhance the model's recognition capabilities. Data is stored in JPG format, organized… See the full description on the dataset page: https://huggingface.co/datasets/Mobiusi/Durian-Plantation-Disease-Leaf-Rot-Detection-Image-Dataset.

sourceHugging Facecc-by-nc-sa-4.0updated 7mo agoView on Hugging Face

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Dataset Card

Durian Plantation Disease Leaf Rot Detection Image Dataset

Ensures high-quality data through multiple rounds of annotation and automated consistency checks, combined with reviews by agricultural pathology experts. The annotation team consists of 10 professionals in agriculture and computer vision. Pre-processing steps include noise reduction, size adjustments, and color normalization to enhance the model's recognition capabilities. Data is stored in JPG format, organized hierarchically in clear file directories. The core advantage of this dataset is an annotation accuracy of up to 95% and excellent consistency, with innovative application of data augmentation techniques such as random cropping and color jittering to enrich training samples and improve recognition robustness. Integrates the latest quality assessment methods, improving model accuracy by 10% over other public agricultural datasets based on industry standards, and significantly reduces false alarm rates. Notably, it includes representative disease images from major durian growing areas, providing the model with a comprehensive perspective. Supports transplantation in different scenarios, reflecting the dataset's scalability and versatility.

Technical Specifications

Field	Type	Description
file_name	string	File name
quality	string	Resolution
disease_presence	boolean	Indicates whether there is a leaf blight disease present in the image.
severity_level	string	Describes the severity of the leaf blight, categorized as mild, moderate, or severe.
affectedareapercentage	float	Percentage of the leaf surface area affected by the leaf blight disease.
leafcolorchange	string	Describes the change in leaf color due to the disease, such as yellowing or browning.
leaf_texture	string	Describes changes in the leaf surface texture, such as dryness or cracking.
affectedleafcount	integer	Number of leaves affected by leaf blight disease in the image.

Compliance Statement

<table> <tr> <td>Authorization Type</td> <td>CC-BY-NC-SA 4.0 (Attribution–NonCommercial–ShareAlike)</td> </tr> <tr> <td>Commercial Use</td> <td>Requires exclusive subscription or authorization contract (monthly or per-invocation charging)</td> </tr> <tr> <td>Privacy and Anonymization</td> <td>No PII, no real company names, simulated scenarios follow industry standards</td> </tr> <tr> <td>Compliance System</td> <td>Compliant with China's Data Security Law / EU GDPR / supports enterprise data access logs</td> </tr> </table>

Source & Contact

If you need more dataset details, please visit Mobiusi. or contact us via contact@mobiusi.com