Image dataset of various soil types in an urban city
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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)
LAR.i实验室——魁北克大学希库蒂米分校（Université du Québec à Chicoutimi, UQAC）于2021年8月24日发布本数据集。 数据集名称：城市多类土壤图像数据集。 已发表的期刊论文：Gensytskyy O.、Nandi P.、Otis M.J.D. 等人的《面向城市行走辅助系统的卷积神经网络土壤摩擦系数估算方法》，刊载于《泛在智能与人性化计算期刊》（Journal of Ambient Intelligence and Humanized Computing）2023年第14卷，页码14291–14307，DOI: 10.1007/s12652-023-04667-w。 本数据集收录各类土壤相关图像，用于"面向城市行走的辅助系统"科研项目。 所有图像均采用智能手机相机以垂直竖拍模式采集，画质优异。 图像文件命名规则为：取对应类别的首字母与尾字母作为标识前缀，后接图像编号。 采集地点为加拿大魁北克省萨格奈市。 本次数据集共包含8个类别，总图像量为493张。 各分类图像数量如下：沥青（Asphalt）89张、混凝土（Concrete）80张、环氧涂层室内地面（Epoxy_coated_interior）34张、草地（Grass）90张、碎石（Gravel）58张、零散积雪（Scrattered_snow）40张、积雪（Snow）68张、木质地面（Wood）34张。
