论文标题
使用事件摄像机图像重建的交通标志检测和识别
Traffic sign detection and recognition using event camera image reconstruction
论文作者
论文摘要
本文介绍了一种基于从事件摄像机提取的信息检测和识别流量标志的方法。该解决方案使用FireNet深卷积神经网络将事件重建为灰度框架。训练了两个Yolov4网络模型，一个基于灰度图像，另一个基于颜色图像。最好的结果是根据灰度图像训练的模型，达到87.03％的效率。
This paper presents a method for detection and recognition of traffic signs based on information extracted from an event camera. The solution used a FireNet deep convolutional neural network to reconstruct events into greyscale frames. Two YOLOv4 network models were trained, one based on greyscale images and the other on colour images. The best result was achieved for the model trained on the basis of greyscale images, achieving an efficiency of 87.03%.
