Adapting Public Annotated Data Sets and Low-Quality Dash Cameras for Spatiotemporal Estimation of Traffic-Related Air Pollution: A Transfer-Learning Approach-Reference-Cited by-同舟云学术

Adapting Public Annotated Data Sets and Low-Quality Dash Cameras for Spatiotemporal Estimation of Traffic-Related Air Pollution: A Transfer-Learning Approach

Published:2024-05 Issue:3 Volume:38 Page:
ISSN:0887-3801
Container-title:Journal of Computing in Civil Engineering
language:en
Short-container-title:J. Comput. Civ. Eng.

Author:

Fei Yu-Hsuan¹,Hsiao Ta-Chih²^ORCID,Chen Albert Y.³^ORCID

Affiliation:

1. Master’s Student, Dept. of Civil Engineering, National Taiwan Univ., Taipei, Taiwan.

2. Professor, Graduate Institute of Environmental Engineering, National Taiwan Univ., Taipei, Taiwan. ORCID:

3. Professor, Dept. of Civil Engineering, National Taiwan Univ., Taipei, Taiwan (corresponding author). ORCID: .

Publisher

American Society of Civil Engineers (ASCE)

Link

https://ascelibrary.org/doi/pdf/10.1061/JCCEE5.CPENG-5667

Reference69 articles.

1. Integrated Framework for Estimating, Benchmarking, and Monitoring Pollutant Emissions of Construction Operations

2. Collaborative distributed decision making for large scale disaster relief operations: Drawing analogies from robust natural systems

3. High-resolution mapping of traffic related air pollution with Google street view cars and incidence of cardiovascular events within neighborhoods in Oakland, CA

4. High-Resolution Air Pollution Mapping with Google Street View Cars: Exploiting Big Data

5. Optimizing the Performance of Energy-Intensive Commercial Buildings: Occupancy-Focused Data Collection and Analysis Approach

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