ID 原文 译文
17985 雨天等恶劣天气会严重影响到图像成像质量，从而影响到视觉处理算法的性能。 Rainy days and other severe weather will seriously affect the image quality, thus affecting the performance of vision processing algorithms.
17986 为了改善雨天图像的成像质量，该文提出一种基于多通道多尺度卷积神经网络的去雨算法，建立了多通道多尺度卷积神经网络结构来提取雨线特征。 In order to improve the imaging quality of rain images, a rainremoval algorithm based on multi-channel multi-scale convolution neural network to extract rain line features isproposed.
17987 首先利用小波阈值引导的双边滤波将有雨图像进行分解，得到高频雨线图像和轮廓保持度高的低频背景图像。 Firstly, the rain images are decomposed by wavelet threshold-guided bilateral filtering to obtain high-frequency rain line images and low-frequency background images with high contour preservation.
17988 然后为了使图像高频部分的雨线信息更为明显，减少雨线特征学习时高频图像中的背景误判，将得到的高频雨线图像再一次通过滤波器得到减弱背景信息同时增强雨线信息的到更高频雨线图像。 Then, in order to make the rain line information in the high-frequency part of the image more obvious and reduce the background misjudgment in the high-frequency image during the rain line feature learning, the obtained high-frequency rain line image is passed through a filter again to obtain a higher-frequency rain line image withreduced background information and enhanced rain line information.
17989 其次针对低频背景图像上也残留了大量雨痕，该文提出将低频背景图像和更高频雨线图像一起送入卷积神经网络进行特征学习，其中对图像提取的是多尺度特征信息，最后得到雨线去除更彻底的复原图像。 Secondly, in view of the large amount ofraindrop imprint left on the low-frequency background image, it is proposed to send the low-frequencybackground image and the higher-frequency rain line image together into the convolution neural network forfeature learning, in which multi-scale feature information is extracted from the image, finally, a more completerestoration image with rain line removal is obtained.
17990 同时在构造网络模型时利用空洞卷积代替标准卷积来提取图像的特征信息，得到更丰富的图像特征，提高了算法的去雨性能。 At the same time, when constructing the network model,hole convolution is used instead of standard convolution to extract the feature information of the image, thus obtaining richer image features and improving the rain removal performance of the algorithm.
17991 从实验结果可以看出去雨之后的图像清晰，细节保持度较高。 From the experimental results, after removing rain, the image is clear and the detail retention is high.
17992 随着城市交通智能化发展，准确高效地获取可用车位对于解决日益严峻的停车难问题至关重要。 With the intelligent development of urban traffic, accurate and efficient access to available parking spaces is essential to solve the increasingly difficult problem of parking difficulties.
17993 该文提出一种基于非局部操作的深度卷积神经网络车位占用检测算法。 Therefore, this paper proposes a deep convolutional neural network parking occupancy detection algorithm based on non-local operation.
17994 针对停车位图像特性，引入非局部操作，度量远距离像素间的相似性，直接获取边缘高频特征； For the image characteristics of parking spaces, non-local operations are introduced, the similaritybetween distant pixels is measured, and the high-frequency features of the edges are directly obtained.