ID 原文 译文
39326 该方法首先利用一种基于卷积神经网络的去雾算法对车牌图片进行去雾预处理，然后将处理过的无雾霾图片送入PLATE-YOLO网络中检测车牌的位置。 Firstly, a deconvolution algorithm based on convolutional neural network is used in the method to defog the license plate image. Then, the processed smog-free image is sent to the PLATE-YOLO network to detect the position of the license plate.
39327 该PLATE-YOLO网络是本文针对车牌检测的特点，对YOLOv3网络做了修改后得到的适用于车牌检测的网络。 The PLATE-YOLO network is a network for license plate detection that has been modified for the YOLOv3 network. The PLATE-YOLO network is suitable for the license plate detection network.
39328 主要改进点有两处:第一，提出了一种基于层次聚类算法的锚盒(Anchor Box)个数和初始簇中心的计算方法; There are two improvement points, one, a method for determining the number of anchor boxes based on hierarchical clustering algorithm is proposed.
39329 第二，针对车牌目标较大的特点，对网络的多尺度特征融合做了优化。 The other, for the characteristics of large license plate targets, the multi-scale feature fusion of the network is optimized.
39330 优化后的PLATE-YOLO网络更适合于车牌检测，且提高了检测速度。 The optimized PLATE-YOLO network is more suitable for license plate detection and improves the detection speed.
39331 实验证明，PLATE-YOLO网络检测车牌的速度较YOLOv3提高了5 FPS; The experiment results show that the PLATE-YOLO network detects the speed of the license plate by 5 FPS compared with the YOLOv3.
39332 在雾霾环境下，经去雾预处理的PLATE-YOLO车牌检测方法比未经去雾处理的车牌检测方法准确率提高了9.2%。 In the smog environment, the PLATE-YOLO network after dehazing pretreatment is more accurate than the unlicensed license plate detection method 9.2%.
39333 毫米波大规模MIMO系统混合预编码是提升无线通信系统容量和降低射频链使用数量的关键技术之一，但是仍然需要大量高精度的相移器实现阵列增益。 Millimeter-wave massive MIMO system hybrid precoding is one of the key technologies to increase the capacity of wireless communication systems and reduce the number of RF chains used, but still requires a large number of high-precision phase shifters to achieve array gain.
39334 为了解决这个问题，本文中，首先通过最大化每个用户的接收信号功率，得到自适应连接结构中射频链与基站天线匹配关系，然后创新地把基于机器学习的自适应交叉熵优化方法应用于1比特量化相移的自适应连接混合预编码器中。 To solve this problem, in this paper, first, by maximizing the received signal power of each user, the matching relationship between the RF chain and the base station antenna in the adaptive connection structure with one-bit quantized phase shifter is obtained, and then the adaptive cross entropy optimization method based on machine learning is innovatively applied to adaptive connection structure in hybrid precoding.
39335 通过减小交叉熵和加入常数平滑参数保证收敛，自适应地更新概率分布以得到几乎最优的混合预编码器。 By reducing the cross-entropy and adding constant smoothing parameter to ensure convergence, the probability distribution is adaptively updated to obtain an almost optimal hybrid precoder.