Results 121 to 130 of about 9,836 (188)

Multimodal generative AI for automated pavement condition assessment: Benchmarking model performance. [PDF]

PLoS One
Xu C, Shu L, Dao A, Cui Y.
europepmc   +1 more source

PY-CrackDB: A pavement crack dataset from paraguayan roads for context-aware computer vision models. [PDF]

Data Brief
Ramírez-Villanueva FG, Vázquez Noguera JL, Legal-Ayala H, Mello-Román JC, Pérez-Estigarribia PE.   +4 more
europepmc   +1 more source

A Physics-Guided Quantitative GPR Framework for Detecting Hanging Sleepers in Ballasted Railway Tracks. [PDF]

Sensors (Basel)
Yang W, Gao J, Xu Z.
europepmc   +1 more source

Alaska University Transportation Center 2012 Annual Report [PDF]

, 2012
Alaska University Transportation Center, University of Alaska Fairbanks   +1 more
core  

Prediction of pavement performance via smatrphone vibration-induced unevenness signature using machine learning. [PDF]

Sci Rep
Wasiq S, Golroo A, Amani MJ, Hajikarimi P.   +3 more
europepmc   +1 more source

University of New Hampshire Stormwater Center 2012 Biennial Report [PDF]

, 2012
University of New Hampshire Stormwater Center (UNHSC)
core   +1 more source

A lightweight YOLO11n seg framework for real time surface crack detection with segmentation. [PDF]

Sci Rep
Tiwari S, Gola KK, Kanauzia R, Gupta GK.
europepmc   +1 more source

Deep spatial attention networks for vision-based pavement distress perception in autonomous driving. [PDF]

PLoS One
Deng F, Jin J.
europepmc   +1 more source

An intelligent YOLO and CNN-BiGRU framework for road infrastructure based anomaly assessment. [PDF]

Sci Rep
Zhumadillayeva A, Ahanger TA, Matkarimov B.   +2 more
europepmc   +1 more source

UNHSC Design Specifications for Porous Asphalt Pavement and Infiltration Beds [PDF]

, 2016
Ballestero, Thomas P., Briggs, Joshua F., Houle, James J., Pochily, Jeff, Puls, Timothy A., Roseen, Robert M., Swenson, Grant   +6 more
core   +1 more source