车辆型号识别系统是利用计算机视觉、图像处理等技术自动识别图像或视频中车辆相关信息的技术系统。 Using machine learning and deep learning algorithms, it learns and identifies visual characteristics such as the car's body shape, lighting, and logo to determine whether the car exists and extracts information such as model, color, and license plate.通过结合各种前沿技术，广泛应用于停车场管理等各个领域，为人们提供了极大的便利。
车辆类型识别系统的工作原理非常微妙。当车辆进入或离开特定识别区域时，入口摄像头快速捕捉车牌号和车辆详细信息。在社区车辆管理场景中，车辆分为固定、临时、不可识别三类，针对每一类采取不同的处理方式。车牌识别系统由多个组件组成，包括摄像设备和地面检测线圈。核心算法包括车牌定位和字符识别。具体流程包括车辆检测等方面。
In the field of artificial intelligence, image structure algorithms based on deep learning networks and convolutional neural networks can accurately detect and identify people, vehicles, and objects in a scene. The LiDAR vehicle model recognition system uses neural network training to collect key parameters such as vehicle length to match vehicle model information.包含激光雷达测距等三大主要模块，数据检测精度高。停车管理云平台巧妙地运用了各种技术，由管理后台等五个部分组成。用户可以通过客户端享受多种便捷的功能。 Vehicle feature information recognition acquires images through the front-end device and completes various identifications based on video analysis and license plate recognition systems.未来可能会实现无人化。
当今市场上有许多先进的车辆模型识别系统。 For example, Beijing Zhongke Huishi Technology Co. Ltd.'s car model recognition product uses machine learning and big data technology to identify multiple car brands and car sub-models.白天车型识别准确率达到90%以上，夜间经过灯光辅助后车型识别准确率达到80%以上。 There is also YOLOV5, a deep learning-based vehicle model detection and recognition system that uses the yoloV5 network architecture to identify six types of vehicle models.
