There are a large number of target data and fewer outlier data in the problem of one-class
classification. The sample reduction methods used for two-class or multi-class classification …

This paper proposes a training points selection method for one-class support vector
machines. It exploits the feature of a trained one-class SVM, which uses points only residing …

Web-scale databases and big data collections are computationally challenging to analyze
and search. Similarity or more precisely nearest neighbor searches are thus crucial in the …

For data pre-processing of SVMs, many scholars tried to find those samples, which would
become support vectors. Generally, support vectors locate in the overlap regions, which are …

Unlike two-class (multi-class) support vector machines, massive targets and few outliers are
available in one-class support vector machine. The strategies to select useful data for two …

For the data processing with increasing avalanche under large datasets, the k nearest
neighbors (KNN) algorithm is a particularly expensive operation for both classification and …

Video stitching fuses multi-camera videos with differing centers of projection into a single
panoramic video. Image registration and video fusion is the key of video stitching. In this …

Genetic Algorithm (GA) has been successfully applied to codebook design for vector
quantization and its candidate solutions are normally turned by LBG algorithm. In this paper …

高维数据集合的最近邻查询性能会受到“维数灾难”(curse of dimensionality) 现象的影响.
提出了一种基于联合聚类的HC2 (hypercube on co-clustering) 高维索引结构 …

Multimedia data is a popular communication medium, but requires substantial storage space
and network bandwidth. Vector quantization (VQ) is suitable for multimedia data applications …