Data · dataset · 2026
Grade-Areca
Listed in Teesside University Research Data Repository
The Arecanut (Areca catechu) RGB Image Dataset is a comprehensive collection of digital images of arecanut kernels captured using conventional RGB imaging techniques.
Description
The dataset provides high-resolution visual information on the external characteristics of arecanut kernels, including their shape, size, colour, surface texture, and other visible quality attributes. It is intended to support the development and evaluation of automated approaches for arecanut quality assessment and grading.
The dataset serves as a valuable resource for researchers and industry practitioners working on computer vision, image processing, machine learning, and deep learning applications in the arecanut industry. The RGB images enable the identification and analysis of visually distinguishable characteristics associated with different grades and quality levels of arecanut kernels. By providing standardized image data, the dataset can facilitate objective and consistent quality assessment while reducing the dependency on subjective manual inspection.
Read the rest (1 more)
The dataset has potential applications in automated grading, quality classification, defect detection, feature extraction, and development of intelligent vision-based inspection systems. It can also be utilized for training and benchmarking machine learning and deep learning models for arecanut image analysis. Overall, the dataset provides a foundation for developing efficient, economical, and scalable computer vision-based solutions for automated arecanut quality inspection and grading.
Links
Where it is published
- DOI doi.org/10.17632/4643p2z67z.2 ↗
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 · Deep learning · 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/4643p2z67z.2 | 9 d 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:461103 | mapping · researchdata tees ac uk | vocabulary-mapper@1.0.0 | keywords['Deep 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: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%) |
| concepts[modality].local:modality:imaging | 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 |