ID 原文 译文
2563 图像分类作为计算机视觉分析领域一个重要的研究方向，其分类性能很大程度上取决于图像的特征表示。 Image classification is an important research direction in the field of computer vision analysis. The key to classification depends largely on the feature representation of the image.
2564 为了能够更好地进行图像分类，本文提出了一种基于局部约束稀疏编码的神经气算法(Neural Gas based Locality-constrained Sparse Coding，NGLSC)用来实现图像分类。 In order to be able to classify images better, this pa-per presents a locality-constrained sparse coding for image classification by introducing ranking locality adaptor as distance regularization.
2565 引入局部排序适配器作为距离正则化约束项已经应用在神经气(Neural Gas，NG)的算法矢量量化中，旨在通过软竞争学习算法来弥补 K 均值聚类(K-means)算法的不足。 The proposed ranking locality adaptor has previously been used in Neural Gas (NG)method for vectorquantization, which originally remedies the K-means by using this soft-competitive learning scheme.
2566 在稀疏编码阶段此算法可求解得到封闭解。 In the new proposedmethod, a closed-form solution can be derived at sparse coding step.
2567 此外，字典更新一般由目标函数的误差项来决定， In addition, dictionary updates are generally determinedby the error term of the objective function.
2568 已有一些经典的算法采用这种方式更新字典。 Some classical algorithms have used this method to update the dictionary.
2569 本文使用 ORL 数据库和 COIL20 数据库将所提出算法和现有算法局部约束线性编码(Locality-constrainedLinear Coding，LLC)，脸元数据学习方法(Metaface Learning，MFL)进行比较。 This paper uses the ORL database and COIL20 database to compare the proposed algorithm with the existing algorithm Locality-constrained Linear Coding, and Metaface Learning algorithm.
2570 实验结果证明本文所提出的算法在图像分类上准确率可达 95% 以上。 The experimental results show that the proposed algorithm has an accuracy of more than 95% in image classification and has stronger performance than the current excellent algorithms.
2571 可以看出，本文为计算机视觉图像分类工作提供了一种有价值的解决思路。 In addition, the recognition rate of the algorithm does not change greatly with the change of the data feature dimension. It can be seen that this paper provides a valuable solution for the classification of computer vision images.
2572 本文提出了有监督的关键词抽取算法———KEING(Keyphrase Extraction using sequentIal patterns withoNe-off and General gaps condition)算法。 Keyphrase extraction using sequential patterns mining with one-off and general gaps condition algorithm(KEING)is proposed in this paper.