Traffic Sign Classification Using Deep and Quantum Neural Networks
Computer Vision and Pattern Recognition
2023-11-14 v1
Abstract
Quantum Neural Networks (QNNs) are an emerging technology that can be used in many applications including computer vision. In this paper, we presented a traffic sign classification system implemented using a hybrid quantum-classical convolutional neural network. Experiments on the German Traffic Sign Recognition Benchmark dataset indicate that currently QNN do not outperform classical DCNN (Deep Convolutuional Neural Networks), yet still provide an accuracy of over 90% and are a definitely promising solution for advanced computer vision.
Cite
@article{arxiv.2209.15251,
title = {Traffic Sign Classification Using Deep and Quantum Neural Networks},
author = {Sylwia Kuros and Tomasz Kryjak},
journal= {arXiv preprint arXiv:2209.15251},
year = {2023}
}
Comments
Accepted for the ICCVG 2022 conference