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Data · dataset · 2025

Cotton Leaf Image Dataset for Disease Classification

Listed in Teesside University Research Data Repository

This dataset comprises high-resolution images of cotton leaves categorized by disease type and health condition.

Description

It is structured into two parts: the Original Dataset and the Augmented Dataset. Original Dataset The original set contains real-world images of cotton leaves affected by various diseases, alongside healthy specimens.

The images are labeled into the following five classes: - Alternaria Leaf Spot: 173 images - Bacterial Blight: 218 images - Fusarium Wilt: 337 images - Healthy Leaf: 333 images - Verticillium Wilt: 312 images Augmented Dataset To enhance diversity and improve model robustness, data augmentation techniques were applied to the original images. The resulting augmented dataset includes: - aug_Alternaria_Leaf: 987 images - aug_Bacterial_Blight: 1027 images - aug_Fusarium_Wilt: 957 images - aug_Healthy_Leaf: 1015 images - aug_Verticillium_Wilt: 977 images This dataset is well-suited for research in plant pathology, machine learning, and image classification tasks related to agriculture and crop health monitoring.

Links

Where it is published

Catalogue records · 1

Topics

Inferred from text
Disease 75% · Image 75%
Provenance · 1 source records, 14 field assertions
SourceKeyLast seenRaw
Teesside University Research Data Repositoryoai:data.mendeley.com/t9hgvk2h9p.17 d agoJSON v1
FieldAssertionExtractorEvidence
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concepts[disease].local:disease:diseaseenrichment · researchdata tees ac ukkeyword-concept-rules@1.0.0title+description (75%)
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