ID 原文 译文
23485 基于变换技术的图像融合是多聚焦图像融合中常采用的方法，其过程是将图像转换到变换域按照一定的融合规则进行融合后再反变换回来，具有较强的抗噪能力，融合效果明显。 Image fusion based on image transform technologies is always used in multi-focus image fusion. It transforms images into transform domain and fuses the transformed image according to a specific fusion rule. After that, the fused image is achieved by the inverse image transform. The transform based image fusion methods are robust to noise and the fused results are widely accepted.
23486 该文提出一种基于离散 Tchebichef 正交多项式变换的多聚焦图像融合方法，首次将离散正交多项式变换应用到多聚焦图像融合领域。 This paper proposes a multi-focus image fusion method based on discrete Tchebichef orthogonal polynomial transform. Discrete orthogonal polynomial transform is firstly introduced to the field of multi-focus image fusion.
23487 该方法成功地利用了图像的空间频率与其离散 Tchebichef 正交多项式变换系数之间的关系，通过离散正交多项式变换系数直接得到空间频率值，避免了将离散多项式变换系数变换到空域计算的过程。 The proposed method combines the spatial frequency with the discrete orthogonal polynomial transform coefficients of image, and it directly achieves the value of spatial frequency by the discrete orthogonal polynomial transform coefficients of the image and avoids the process of recalculation that transforms the discrete orthogonal polynomial transform coefficients to space domain.
23488 所提方法节省了融合时间，并提高了融合效果。 The proposed method can reduce the fusing  time in multi-focus image fusion and improves the fusion effect.
23489 针对传统无线局域网(WLAN)室内定位系统中因参考点密集分布及逐点信号采集所带来的位置指纹数据库构建工作量繁重的问题，该文提出一种基于混合半监督流形学习和 3 次样条插值的数据库构建方法。 To deal with the high cost involved in the location fingerprint database construction due to the dense Reference Points (RPs) distribution and point-by-point Received Signal Strength (RSS) collection in the conventional Wireless Local Area Network (WLAN) indoor localization systems, a new database construction approach based on the integrated semi-supervised manifold learning and cubic spline interpolation is proposed.
23490 该方法利用少量标记数据和大量未标记数据求解定位目标函数的最优解，同时根据高维信号强度空间与低维物理位置空间的映射关系，实现对未标记数据的位置标定。 The proposed approach utilizes a small amount of labeled data and a massive amount of unlabeled data to find the optimal solution to localization target function, and meanwhile relies on the mapping relations between the high-dimensional signal strength space and low-dimensional physical location space to calibrate the unlabeled data with location coordinates.
23491 大量实验结果表明，该方法能够在保证较高定位精度的同时，显著降低位置指纹数据库的构建开销。 The extensive experiments demonstrate that the proposed approach is able to guarantee the high localization accuracy, as well as significantly reduce the cost involved in location fingerprint database construction.
23492 该文针对现有推荐算法在面对托攻击时鲁棒性不高的问题，提出一种基于模糊核聚类和支持向量机的鲁棒推荐算法。 The existing collaborative recommendation algorithms have low robustness against shilling attacks. To solve this problem, a robust collaborative recommendation algorithm is proposed based on Fuzzy Kernel Clustering (FKC) and Support Vector Machine (SVM).
23493 首先，根据攻击概貌间高度相关的特性，利用模糊核聚类方法在高维特征空间对用户概貌进行聚类，实现攻击概貌的第 1 阶段检测。 Firstly, according to the high correlation characteristic between attack profiles, the FKC method is used to cluster user profiles in high-dimensional feature space, which is the first stage of the attack profile detection.
23494 然后，利用支持向量机分类器对含有攻击概貌的聚类进行分类，实现攻击概貌的第 2阶段检测。 Then, the SVM classifier is used to classify the cluster including attack profiles, which is the second stage of the attack profile detection.