TY -的A2 Alonso-Betanzos帕罗盟,肖董AU - Li Hongzong盟——刘Chenyi盟——他,Qifei PY - 2019 DA - 2019/10/13 TI -大卡车安全预警系统基于轻量级SSD模型SP - 2180294六世- 2019 AB -交通开采过程中的重要一环,而大型卡车是矿山运输的重要工具之一。大型卡车由于体积大，行驶位置小，存在盲点，是矿山安全运输的隐患，对生产效率和经济损失有很大影响。传统的大型卡车安全预警系统主要采用超声波短距离测距法、雷达测距法、GPS(全球定位系统)等技术。这些方法的缺点是受环境和天气的影响，不能实时显示对象状态。因此，实现基于机器视觉的大型卡车安全预警系统变得越来越重要。为此，本文提出了一种轻型SSD (Single Shot MultiBox Detector, Single Shot MultiBox Detector)模型和一种atrous卷积模型来构建大型卡车目标识别模型。首先，对训练图像进行采集和标记。然后，利用轻量级SSD模型建立目标识别模型。为了提高小目标检测精度，引入了atrous卷积层。 In the end, the objectness prior method is used to improve the classification speed. Experimental results show that, compared with the original SSD model, the lightweight SSD model occupies less space and runs faster. The lightweight SSD model with the atrous convolutional layer is more sensitive to small objects and improves detection accuracy. The objectness prior method further improves the identification speed. Compared with the traditional large truck safety warning, the system is not affected by the environment and realizes the visualization of large truck safety warning. SN - 1687-5265 UR - https://doi.org/10.1155/2019/2180294 DO - 10.1155/2019/2180294 JF - Computational Intelligence and Neuroscience PB - Hindawi KW - ER -