Data · dataset · 2025
Kazakh Banknote Image Dataset
Listed in Teesside University Research Data Repository
This dataset contains images of Kazakh banknotes across seven denominations: 500, 1000, 2000, 5000, 10000, 20000, and a mixed category (Mix) containing multiple denominations within the same image.
Description
Each denomination folder includes at least 100 images, with the exception of the Mix folder, which contains more than 1000 images. The banknotes are photographed against various backgrounds, providing diversity in lighting and scene conditions.
The 5000 KZT denomination is further divided into three subcategories: - 5000_new_single — each image contains a single new banknote, - 5000_new — images with multiple new-design banknotes, - 5000_old — images with multiple old-design banknotes. Most images contain multiple banknotes of the same denomination, except in the 5000_new_single subset. File names follow a numeric sequence (000001.jpg, 000002.jpg, …).
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The dataset is designed for research in computer vision, including: - banknote classification, - object detection in images with multiple notes, - studies on dataset diversity, transfer learning, and robustness of deep learning models in currency recognition tasks. All images were collected and curated specifically for research purposes. The dataset does not contain any personal or sensitive information.
Links
Where it is published
- DOI doi.org/10.17632/gyw87k93yb.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
- Artificial intelligence · Computer Science & AI · Computer vision · Earth & Environmental Science · Pattern recognition
- Inferred from text
- Image 75%
Provenance · 1 source records, 11 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| Teesside University Research Data Repository | oai:data.mendeley.com/gyw87k93yb.1 | 14 h ago | JSON v1 |
| Field | Assertion | Extractor | Evidence |
|---|---|---|---|
| access_level | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[field].anzsrc:field:460304 | mapping · researchdata tees ac uk | vocabulary-mapper@1.0.0 | keywords['Computer Vision'] |
| concepts[field].anzsrc:field:460308 | mapping · researchdata tees ac uk | vocabulary-mapper@1.0.0 | keywords['Pattern Recognition'] |
| concepts[field].anzsrc:group:4602 | mapping · researchdata tees ac uk | vocabulary-mapper@1.0.0 | keywords['Artificial Intelligence'] |
| 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[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 |