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
- DOI doi.org/10.17632/t9hgvk2h9p.1 ↗
DOI / persistent id · from researchdata tees ac uk
Catalogue records · 1
- OAI-PMH record data.mendeley.com/oai?verb=GetRecord&metadataPrefix=oai_dc&identifier=oai%3Adata… ↗
metadata API · from researchdata tees ac uk
Topics
- From keywords
- Computer Science & AI · Computer vision · Earth & Environmental Science · Engineering · Humanities · Life Sciences · Social Science
Provenance · 1 source records, 14 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| Teesside University Research Data Repository | oai:data.mendeley.com/t9hgvk2h9p.1 | 7 d ago | JSON v1 |
| Field | Assertion | Extractor | Evidence |
|---|---|---|---|
| access_level | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[disease].local:disease:disease | enrichment · researchdata tees ac uk | keyword-concept-rules@1.0.0 | title+description (75%) |
| concepts[field].anzsrc:field:460304 | mapping · researchdata tees ac uk | vocabulary-mapper@1.0.0 | keywords['Computer Vision'] |
| concepts[field].local:field:computer-science-ai | mapping · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[field].local:field:earth-environmental | mapping · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[field].local:field:engineering | mapping · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[field].local:field:humanities | mapping · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[field].local:field:life-sciences | mapping · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[field].local:field:social-science | mapping · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[modality].local:modality:image | enrichment · researchdata tees ac uk | keyword-concept-rules@1.0.0 | title+description (75%) |
| description | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | /metadata/dc/description |
| license | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | /metadata/dc/rights |
| publication_date | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| title | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | /metadata/dc/title |