Image dataset of various soil types in an urban city
- Description:
- LAR.i Laboratory - Université du Québec à Chicoutimi (UQAC)
2021-08-24
Name: Image dataset of various soil types in an urban city
Published journal paper: Gensytskyy, O., Nandi, P., Otis, M.JD. et al. Soil friction coefficient estimation using CNN included in an assistive system for walking in urban areas. J Ambient Intell Human Comput 14, 14291–14307 (2023). https://doi.org/10.1007/s12652-023-04667-w This dataset contains images of various types of soils and was used for the project "An assistive system for walking in urban areas". The images were taken using a smartphone camera in a vertical orientation and are high-quality.
The files are named with two characters, being the first letter and last letter of its class name, following by their number.
Capture location : City of Saguenay, Quebec Canada.
Class count : 8
Total number of images : 493
Classes and number of images per class:- Asphalt (89)
- Concrete (80)
- Epoxy_coated_interior (34)
- Grass (90)
- Gravel (58)
- Scrattered_snow (40)
- Snow (68)
- Wood (34)
- , , and Otis, Martin J.-D.
- Contributor(s):
- Gensytskyy, Oleksiy and Otis, Martin
- Source Repository:
- Dataverse de l'Université du Québec à Chicoutimi
- Series:
- Martin Otis Dataverse // Laboratoire d’Automatique et de Robotique interactive (LAR.i) Dataverse
- Publisher(s):
- Borealis
- Access:
- Public
- URL:
- https://doi.org/10.5683/SP3/R8FDJB
- Publication date:
- 2021-10-14
- Subjects:
- Keywords:
- Identifier:
- https://doi.org/10.5683/SP3/R8FDJB
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