Data · dataset · 2022
Sun Flower Fruits and Leaves dataset for Sunflower Disease Classification through Machine Learning and Deep Learning
Listed in Teesside University Research Data Repository
(1) The world economy largely depends on vegetable production, whereas The sunflower (Helianthus annuus) is an annual plant with a sizeable daisy-like flower face.
Description
Because of the early disease recognition of sunflower, the farmer cannot produce high yield and face economic loss. (2) In the recent era, image classification and detection is crucial application of Computer Vision.
(3) In this dataset, two types files of Sunflower images are included, namely the original image file and the augmented image file. Three types of diseases, namely downy mildew, leaf scars, and Gray Mold, exist in every file. Besides, the fresh leaves image of a sunflower is also included.
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(4) A total of four hundred and sixty-seven images (467) are collected from the sunflower garden contained in the original image file. Then the augmentation operation is performed to boost the images, and a total of one thousand and six hundred sixty-six (1668) images are contained in the augmented image file. (5) The images of sunflower (disease-affected and disease-free) are assembled from the Bangladesh Agricultural Research Institute (BARI) demonstration farm at Gazipur with the help of domain expects.
Links
Where it is published
- DOI doi.org/10.17632/b83hmrzth8.1 ↗
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 · Image processing
Provenance · 1 source records, 11 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| Teesside University Research Data Repository | oai:data.mendeley.com/b83hmrzth8.1 | 20 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:460306 | mapping · researchdata tees ac uk | vocabulary-mapper@1.0.0 | keywords['Image Processing'] |
| 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 |