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Yingxiang Zhao, Lumei Zhou, Xiaoli Wang, Fan Wang and Gang Shi
Cracks are a common type of road distress. However, the traditional manual and vehicle-borne methods of detecting road cracks are inefficient, with a high rate of missed inspections. The development of unmanned aerial vehicles (UAVs) and deep learning ha...
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Yumin Tan and Yunxin Li
The timely and proper rehabilitation of damaged roads is essential for road maintenance, and an effective method to detect road surface distress with high efficiency and low cost is urgently needed. Meanwhile, unmanned aerial vehicles (UAVs), with the ad...
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Antonella Ragnoli, Maria Rosaria De Blasiis and Alessandro Di Benedetto
The road pavement conditions affect safety and comfort, traffic and travel times, vehicles operating cost, and emission levels. In order to optimize the road pavement management and guarantee satisfactory mobility conditions for all road users, the Pavem...
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Carl Van Geem, Marleen Bellen, Boris Bogaerts, Bart Beusen, ... Peter Hellinckx
Pág. 2966 - 2975
This contribution presents the results of the ?SENSOVO? project initiated by the Flanders Institute for Mobility (VIM), executed by the University of Antwerp (UAntwerp), the Flemish Institute for Technological Research (VITO) and the Belgian Road Researc...
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