Truck Axle Detection with Convolutional Neural Networks. (arXiv:2204.01868v1 [cs.CV])

Axle count in trucks is important to the classification of vehicles and to
the operation of road systems, and is used in the determination of service fees
and the impact on the pavement. Although axle count can be achieved with
traditional methods, such as manual labor, it is increasingly possible to count
axles using deep learning and computer vision methods. This paper aims to
compare three deep learning object detection algorithms, YOLO, Faster R-CNN and
SSD, for the detection of …

arxiv convolutional neural networks cv detection networks neural networks truck