深度学习研究现状及其在轨道交通领域的应用

Deep Learning and Its Application in the Field of Rail Transit

深度学习在特征提取与图像识别方面有巨大的潜力和优势,近年来其在轨道交通领域的应用研究受到了越来越多的关注。文章详细介绍了深度学习在司机身份识别、疲劳检测、车道线检测以及车辆设备故障检测等方面的应用研究现状,总结了其在轨道交通领域应用中的主要作用和存在的问题,并展望了其未来值得研究的方向。

Deep learning has shown great potential and advantage in feature extraction and image recognition. In recent years, more and more researches have focused on the application of deep learning in rail transit. It introduced the current state of deep learning and its application in the field of rail transit, including identification, driver fatigue detection, lane detection and vehicle recognition equipment fault detection. Additionally, it summarized the main functions and existing problems of deep learning in the field of rail transit, and presented some prospects of future work.