Results 161 to 170 of about 9,758 (177)

TIGPR: A multi-view ground penetrating radar detection data for damage assessment of transportation infrastructure. [PDF]

Data Brief
Liu Z, Cui B, Gu X.
europepmc   +1 more source

Development of a novel ensemble learning model for predicting asphalt volumetric properties using experimental data for pavement performance assessment. [PDF]

Sci Rep
Khiavi AJ, Naeim B, Soleimanzadeh M.
europepmc   +1 more source

Crack-MsCGA: A Deep Learning Network with Multi-Scale Attention for Pavement Crack Detection. [PDF]

Sensors (Basel)
Liu G, Wu X, Dai F, Liu G, Li L, Huang B.   +5 more
europepmc   +1 more source

Leveraging a deep learning generative model to enhance recognition of minor asphalt defects. [PDF]

Sci Rep
Cano-Ortiz S, Sainz-Ortiz E, Lloret Iglesias L, Martínez Ruiz Del Árbol P, Castro-Fresno D.   +4 more
europepmc   +1 more source

Lightweight deep learning for real-time road distress detection on mobile devices. [PDF]

Nat Commun
Hu Y, Chen N, Hou Y, Lin X, Jing B, Liu P.   +5 more
europepmc   +1 more source

YOLO-RD: A Road Damage Detection Method for Effective Pavement Maintenance. [PDF]

Sensors (Basel)
Wang W, Yu X, Jing B, Tang Z, Zhang W, Wang S, Xiao Y, Li S, Yang L.   +8 more
europepmc   +1 more source

A Review of Vision-Based Pothole Detection Methods Using Computer Vision and Machine Learning. [PDF]

Sensors (Basel)
Safyari Y, Mahdianpari M, Shiri H.
europepmc   +1 more source

Sustainable Cold Mix Asphalt: A Comprehensive Review of Mechanical Innovations, Circular Economy Integration, Field Performance, and Decarbonization Pathways. [PDF]

Materials (Basel)
Malik MD, Chen Y, Mu J, Dong R.
europepmc   +1 more source

Pavement crack identification method based on IOtsu-Dd algorithm. [PDF]

PLoS One
Yang Y, Wang L, Xiong Q.
europepmc   +1 more source

Algorithm for pixel-level concrete pavement crack segmentation based on an improved U-Net model. [PDF]

Sci Rep
Zhang Z, He Y, Hu D, Jin Q, Zhou M, Liu Z, Chen H, Wang H, Xiang X.   +8 more
europepmc   +1 more source