ID 原文 译文
16455 最后，公共数据集上进行的一系列相关实验表明ASSD算法有效提高了传统SSD算法的检测精度，尤其适用于小目标检测。 Finally, a series of experiments on thecommon data set show that the ASSD algorithm effectively improves the detection accuracy of conventionalSSD algorithm, especially for small object detection.
16456 针对全变分(TV)算法梯度效应造成图像纹理细节丢失和单像素成像系统中的环境噪声问题，该文给出基于高斯平滑压缩感知分数阶全变分(FOTVGS)算法的图像重构。 In view of the gradient effect caused by the gradient effect of the Total Variation (TV) algorithm and the environmental noise in the single pixel imaging system, an image reconstruction based on the GaussianSmooth compressed sensing Fractional Order Total Variation algorithm (FOTVGS) is proposed.
16457 分数阶微分损失图像低频分量的同时增加了图像的高频分量，达到增强图像细节的目的，高斯平滑滤波算子更新拉格朗日梯度算子滤除了微分算子导致的加性高斯白噪声高频分量的增加。 Fractionaldifferential loss of low-frequency components of the image increases the high-frequency components of the imageto achieve the purpose of enhancing image details. The Gaussian smoothing filter operator updates the Lagrangian gradient operator to filter out the additive white Gaussian noise caused by the differential operator.
16458 仿真结果表明，对比其他4种同类算法，在相同的采样率和噪声水平下，该算法能取得最大的峰值信噪比(PSNR)和结构相似度(SSIM)。 Simulation results show that, compared with other four similar algorithms, the algorithm can achieve themaximum Peak Signal-to-Noise Ratio (PSNR) and Structural SIMilarity(SSIM) at the same sampling rate andnoise level.
16459 采样率为0.2时，对比分数阶全变分(FOTV)算法，在无噪声(测量值)和有噪声(测量值)情况下提高的最大峰值信噪比和结构相似度分别是1.39 dB(0.035)和3.91 dB(0.098)。 When the sampling rate is 0.2, compared with the Fractional Order Total Variation (FOTV)algorithm, the maximum PSNR and SSIM increase by 1.39 dB (0.035) and 3.91 dB (0.098) respectively.
16460 可见，此算法在无噪声和有噪声情况下均能提高图像的重构质量，尤其是在有噪声情况下对图像重构质量有较大提高。 It canbe proved that this algorithm can improve the reconstruction quality of the image in the absence of noise andnoise, especially in the case of noise, the quality of image reconstruction is greatly improved.
16461 该算法为单像素成像等计算成像系统中由于环境造成的噪声的图像重构提供了可行的解决方案。 The proposedalgorithm provides a feasible solution for image reconstruction of noise caused by environment in single-pixelimaging and other computing imaging system.
16462 随着地铁乘客的大量增加，实时准确地监测地铁站内客流量对于保证乘客安全具有重要意义。 With the large increase of passengers in metro stations, precise and real-time monitoring of passengerflow in subway stations is of great significance for ensuring passenger safety.
16463 针对地铁场景复杂、行人目标小等特点，该文提出了多尺度加权特征融合(MWF)网络，实现地铁客流量的精准实时监测。 Based on the features ofcomplicated subway scenes and small pedestrian targets, a Multi-scale Weighted Feature (MWF) fusionnetwork to achieve accurate real-time monitoring of subway passengers is proposed.
16464 在数据预处理阶段，该文提出过采样目标增强算法，对小目标占比不足的图片进行拼接处理，增加小目标在训练时的迭代频率。 In the data preprocessing stage, an oversampling target enhancement algorithm is proposed to stitch the pictures with an insufficient proportion of small targets to increase the iteration frequency of small targets during training.