ID 原文 译文
40136 实验结果表明，以熵、标准差、平均梯度、清晰度和空间频率作为客观评价指标，与基于拉普拉斯金字塔变换等经典融合算法相比均有所提升。 The experimental results show that the proposed method can improve fusion results in terms of entropy, standard deviation, average gradient, clarity and spatial frequency, compared with classical fusion algorithms including the methods based on the Laplace pyramid transformation.
40137 本文研究方法性能优越，丰富了融合图像的细节信息，可获得更高质量的DR融合图像。 Our method can extend image-fusion performance by enriching the detailed information of the images and obtaining higher quality.
40138 红外图像诊断是电力系统故障诊断的重要方式，但目前仍依靠人工辅助框图来实施图像中目标的检测。 Infrared fault image recognition is an important method to diagnose electrical equipment, but the recognition relies on the manually created bounding boxes over objects.
40139 为提升检测效率，本文借鉴并改进在目标分割任务中表现优异的Mask-RCNN方法，利用图像自动语义分割识别红外图像中的一个或多个电力设备，并提取设备轮廓。 In this paper, in order to improve the detection efficiency, automatic semantic segmentation of infrared images is investigated to recognize one or more electrical equipment objects.
40140 为了缓解标注样本相对不足的问题，研究Mask-RCNN的迁移学习机制，设计并实现了训练数据重要性采样、参数迁移映射等方法，使改进后的方法适应于红外图像电力设备检测任务。 The proposed method is based on Mask-RCNN which has demonstrated good performance on instance segmentation.Our main contribution is applying transfer learning to Mask-RCNN, where importance sampling and parameter mapping are conducted to alleviate the data-shortage problem on pixel-level annotating.
40141 在实际采集数据集上的实验表明，改进后的算法能在仅有少量像素级标注样本的条件下，较好地提取出电力设备的轮廓，并进一步识别出设备类别。 Experimental results on real-world datasets have shown that the improved version of Mask-RCNN is able to extract the shapes of electrical equipment, even with limited data with pixel-level annotations.
40142 所提模型和算法为进一步的设备分区和故障区域检测提供了精确有效的预处理手段。 The proposed algorithm provides an efficient way to the subsequent steps of fault region detection and classification.
40143 在深入研究可变长扩频因子（Orthogonal variable spreading factor，OVSF）码递归构造原理、码树结构模型、数学理论基础以及分配原则的基础上，针对宽带码分多址（Wideband code division multiple access，WCDMA）信号非合作接收情况，提出了一种基于快速沃尔什-哈达玛变换的OVSF码盲识别算法。 Based on the in-depth study of the recursive construction principle, code tree structure model, mathematical theory foundation and distribution principle of orthogonal variable spreading factor(OVSF)code, a blind recognition algorithm based on fast walsh-hadamard transform for non-cooperative reception of wideband code division multiple access(WCDMA)signals is proposed.
40144 该算法利用OVSF码的继承关系、正交特性以及数据的循环移位，并结合快速沃尔什-哈达玛变换，消除了数据解扩模糊性，降低了计算复杂度。 By using the inheritance relation and orthogonal property of OVSF code as well as the cyclic shift of data, and combining with the fast walsh-hadamard transform, the proposed algorithm eliminates the ambiguity of de-spreaded data and reduces the computational complexity.
40145 理论分析和实验结果表明：本文算法在非合作和无先验信息以及低信噪比情况下，可对WCDMA系统下行信道中的多个OVSF码进行快速解扩与盲识别，具有很好的可靠性、有效性和实用性。 Theoretical analysis and experimental results show that the proposed algorithm can perform rapid de-spread and blind recognition of multiple OVSF codes in the downlink channel of the WCDMA system under the conditions of non-cooperation, no prior information and low signal-tonoise ratio, which is very reliable, effective and practical.