Data · dataset · 2024
Annotated Sugarcane Plants
Listed in Teesside University Research Data Repository
Description
Ubaid, M.T.; Javaid, S. Precision Agriculture: Computer Vision-Enabled Sugarcane Plant Counting in the Tillering Phase. Journal of Imaging 2024, 10, 102. doi.org/10.3390/jimaging10050102 Description Plant annotation is the process of identifying and naming certain aspects or characteristics of plant species, usually for research, categorization, or agriculture. This technique is frequently done out manually by specialists or using automated systems that employ picture recognition technologies.
Annotations give useful information on plants' morphology, phenology, diseases, and genetic characteristics. They may include labels for anatomical structures. Annotations may also include categorizing plants based on their development stage, health status, or species identification.
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Plant annotations are used in agriculture to monitor crop development, detect pests and diseases, optimize cultivation practices, and improve production estimates. Additionally, annotated plant datasets are useful resources for training machine learning models for automated plant recognition and analysis tasks. The images were labeled using the labeling tool "labelImg".
The cane under the leaves was labeled. Annotating the images was difficult because the cane section was so little. Labeling needs care and accuracy while drawing a bounded box around the cane.
For 175 photos of data, around 18650 bounding boxes were drawn. The bounding boxes were allocated the class name "sugarcane".
Links
Where it is published
- DOI doi.org/10.17632/ydr8vgg64w.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 · Earth & Environmental Science · Life Sciences
Provenance · 1 source records, 10 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| Teesside University Research Data Repository | oai:data.mendeley.com/ydr8vgg64w.2 | 16 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].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 (65%) |
| 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 |