Data · dataset · 2026
Agri-Vision4: A Comprehensive Multi-Crop Leaf Disease Dataset of Tomato, Papaya, Zucchini, and Bottle Gourd from Bangladesh
Listed in Teesside University Research Data Repository
Agri-Vision4 is an expert-validated multi-crop leaf disease dataset developed for computer vision and precision agriculture research, comprising 5,180 original images and 28,000 augmented images across 28 disease and healthy classes from four major crops: Bottle Gourd, Papaya, Tomato, and Zucchini.
Description
The original dataset is divided into 3,615 training images (70%), 762 testing images (15%), and 803 validation images (15%).
To address class imbalance, augmentation techniques were applied to expand each of the 28 classes to 1,000 images, resulting in a balanced augmented dataset of 28,000 images. Images were collected under real-world agricultural conditions in Bangladesh using a SONY α7 II camera and standardized to 512×512 pixels. The augmented dataset provides a balanced representation across all disease and healthy classes, supporting robust model training and evaluation.
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Overall, Agri-Vision4 provides a diverse and balanced resource for plant disease classification, agricultural image analysis, computer vision, and deep learning–based precision agriculture research.
Links
Where it is published
- DOI doi.org/10.17632/8t6k37ztxc.3 ↗
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 · Deep learning · Earth & Environmental Science · Life Sciences · Machine learning
Provenance · 1 source records, 13 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| Teesside University Research Data Repository | oai:data.mendeley.com/8t6k37ztxc.3 | 15 h 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].anzsrc:field:461103 | mapping · researchdata tees ac uk | vocabulary-mapper@1.0.0 | keywords['Deep Learning'] |
| concepts[field].anzsrc:group:4611 | mapping · researchdata tees ac uk | vocabulary-mapper@1.0.0 | keywords['Machine Learning'] |
| 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:life-sciences | 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 |