Deep-Learning-Based Approach for Automated Detection of Irregular Walking Surfaces for Walkability Assessment with Wearable Sensor

Autor: Hui R. Ng, Xin Zhong, Yunwoo Nam, Jong-Hoon Youn

Publikováno v: Applied Sciences, Vol 13, Iss 24, p 13053 (2023)

A neighborhood’s walkability is associated with public health, economic and environmental benefits. The state of the walking surface on sidewalks is a key factor in assessing walkability, as it promotes pedestrian movement and exercise. Yet, conven

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Machine Learning Approach for Automated Detection of Irregular Walking Surfaces for Walkability Assessment with Wearable Sensor.

Autor: Ng HR; Department of Computer Science, University of Nebraska Omaha, Omaha, NE 68182, USA., Sossa I; Department of Computer Science, University of Nebraska Omaha, Omaha, NE 68182, USA., Nam Y; Community and Regional Planning, University of Nebraska-Lincoln, Lincoln, NE 68588, USA., Youn JH; Department of Computer Science, University of Nebraska Omaha, Omaha, NE 68182, USA.

Publikováno v: Sensors (Basel, Switzerland) [Sensors (Basel)] 2022 Dec 24; Vol. 23 (1). Date of Electronic Publication: 2022 Dec 24.