Data · dataset · 2022
Dataset for Drone-based Inspection of Road Pavement Structures for Cracks
Listed in Teesside University Research Data Repository
The dataset is available online as a benchmarking dataset for drone-based inspection of pavement structures.
Description
The data were acquired in an experimental road with a length of 386 meters, belonging to Montmorency Forest laboratory of Université Laval, located in North of Quebec City, on 2021/06/16. The road is mainly used for testing pavement paints, laying techniques, and inspection simulations.
A DJI MINI 2 drone was employed to collect images for this dataset. The drone has a 12 megapixels camera with an 83 degrees field of view, capturing 1920 x 1080 images in the continuous recording mode. The drone performs six passes on an experimental road at different altitudes and horizontal speeds.
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The drone was controlled manually, and the footage was acquired using the embedded camera that stabilized and controlled using the drone's gimbal. Moreover, after data acquisition, the length and width of some cracks and road landmarks were measured for evaluating crack characterization. **** In case of any use, please cite this dataset and our paper ****
Links
Where it is published
- DOI doi.org/10.17632/csd32bm8zx.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 · Deep learning · Earth & Environmental Science · Engineering · Humanities · Life Sciences · Social Science
- Inferred from text
- Image 65%
Provenance · 1 source records, 13 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| Teesside University Research Data Repository | oai:data.mendeley.com/csd32bm8zx.1 | 11 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 (65%) |
| 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 |