Borealis
Gensytskyy, Oleksiy;
Ben Ayed, Yessine;
Otis, Martin J.-D.
—
2021-10-14
<b>LAR.i Laboratory - Université du Québec à Chicoutimi (UQAC)</b><br>
2021-08-24<br>
Name: Image dataset of various soil types in an urban city<br><br>
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.<br>
The files are named with two characters, being the first letter and last letter of its class name, following by their number.<br><br>
Capture location : City of Saguenay, Quebec Canada.<br>
Class count : 8<br>
Total number of images : 493<br><br>
Classes and number of images per class:
<ul>
<li>Asphalt (89) </li>
<li>Concrete (80)</li>
<li>Epoxy_coated_interior (34)</li>
<li>Grass (90)</li>
<li>Gravel (58)</li>
<li>Scrattered_snow (40)</li>
<li>Snow (68)</li>
<li>Wood (34)</li>
</ul>