论文标题
使用安装在车辆上的相机对物体检测和识别交换体的识别
Object Detection and Recognition of Swap-Bodies using Camera mounted on a Vehicle
论文作者
论文摘要
对象检测和识别是计算机视觉的挑战领域，也是自动驾驶汽车的基本要求。该项目旨在共同执行交换体的对象检测，并使用有效的光学特征识别（OCR）方法通过读取ILU代码来找到交换体的类型。最近的研究活动已大大改进了深度学习技术，这证明可以增强计算机视野。收集足够的图像来训练模型是取得良好结果的关键一步。从不同位置收集了培训数据，并解释了细节。此外，事实证明，用于培训的数据增强方法可有效提高受过训练的模型的性能。训练该模型取得了良好的结果，还提供了测试结果。最终模型通过图像和视频进行了测试。最后，本文还引起了人们对项目各个阶段和可能采用的解决方案所面临的一些主要挑战的关注。
Object detection and identification is a challenging area of computer vision and a fundamental requirement for autonomous cars. This project aims to jointly perform object detection of a swap-body and to find the type of swap-body by reading an ILU code using an efficient optical character recognition (OCR) method. Recent research activities have drastically improved deep learning techniques which proves to enhance the field of computer vision. Collecting enough images for training the model is a critical step towards achieving good results. The data for training were collected from different locations with maximum possible variations and the details are explained. In addition, data augmentation methods applied for training has proved to be effective in improving the performance of the trained model. Training the model achieved good results and the test results are also provided. The final model was tested with images and videos. Finally, this paper also draws attention to some of the major challenges faced during various stages of the project and the possible solutions applied.
