Deep learning-based predictive models for pavement patching and manholes evaluation
Author:
Affiliation:
1. Department of Civil and Environmental Engineering, Amirkabir University of Technology (Tehran Polytechnic), Tehran, Iran
Publisher
Informa UK Limited
Link
https://www.tandfonline.com/doi/pdf/10.1080/10298436.2024.2349901
Reference21 articles.
1. ASTM, 2018. Astm D 6433-18 standard practice for roads and parking lots pavement condition index surveys. Conshohocken, PA, USA: ASTM International West.
2. Comparison of methods and equipment to conduct pavement distress surveys;Benson K.R.;Transportation Research Record,1988
3. Commandre B. et al. 2017. Manhole cover localization in aerial images with a deep learning approach. In: ISPRS Hannover Workshop: HRIGI 17–CMRT 17–ISA 17–EuroCOW 17. 333–338.
4. Pavement distress detection and classification based on YOLO network
5. Automated detection of pavement patches utilizing support vector machine classification
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