Weather and surface condition detection based on road-side webcams utilizing AlexNet, GoogleLeNet, and ResNet: Application of pre-trained Convolutional Neural Network

Author:

Khan Md Nasim,Ahmed Mohamed M.

Funder

Wyoming Department of Transportation

Publisher

Elsevier BV

Subject

Management, Monitoring, Policy and Law,Transportation,Automotive Engineering,Civil and Structural Engineering

Reference41 articles.

1. Detecting realtime snowy weather on freeways based on machine vision and vehicle kinamatics: a non-parametric data fusion technique;Ali,2020

2. Andrey, J., Mills, B., Leahy, M., Suggett, J., 2003. Weather as a Chronic Hazard for Road Transportation in Canadian Cities 319–343.

3. Application of deep learning technique to manage COVID-19 in routine clinical practice using CT images: results of 10 convolutional neural networks;Ardakani;Comput. Biol. Med.,2020

4. Comparison of deep learning models for determining road surface condition from roadside camera images and weather data;Carrillo;Proc. Artif. Intell. Mach. Learn. Smart Mobil. Sess.,2019

5. Federal Highway Administration, 2020. How Do Weather Events Impact Roads? - FHWA Road Weather Management [WWW Document]. URL http://www.ops.fhwa.dot.gov/weather/q1_roadimpact.htm (accessed 9.20.19).

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