Scalable Label-efficient Footpath Network Generation Using Remote Sensing Data and Self-supervised Learning-Reference-Cited by-同舟云学术

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Scalable Label-efficient Footpath Network Generation Using Remote Sensing Data and Self-supervised Learning

Published:2023-11-28 Issue: Volume:2 Page:137-144
ISSN:
Container-title:2023 International Conference on Digital Image Computing: Techniques and Applications (DICTA)
language:
Short-container-title:

Author:

Wanyan Xinye¹,Seneviratne Sachith¹,Nice Kerry¹,Thompson Jason¹,White Marcus²,Langenheim Nano¹,Stevenson Mark¹

Affiliation:

1. University of Melbourne,Transport, Health, and Urban Design Research Lab, Melbourne School of Design,Australia

2. Swinburne University of Technology,Centre for Design Innovation,Australia

Funder

University of Melbourne

Australian Government

Medical Research Council

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10410651/10410903/10410965.pdf?arnumber=10410965

Reference27 articles.

1. Many Pathways from Land Use to Health: Associations between Neighborhood Walkability and Active Transportation, Body Mass Index, and Air Quality

2. Walkability: what is it?;Lo;Journal of Urbanism,2009

3. Mapping the walk: A scalable computer vision approach for generating sidewalk network datasets from aerial imagery

4. WHY ARE PEOPLE STILL NOT WALKING? THE NEED FOR A MICRO-SCALED MULTI-CRITERIA SPATIO-TEMPORAL DESIGN APPROACH TO IMPROVE WALK-QUALITY

5. Urban Footpath Image Dataset to Assess Pedestrian Mobility

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