InfoSphere Warehouse USES a particularly powerful method for deviation detection that is based on data clustering.
InfoSphere Warehouse使用一种特别强大的方法来进行偏差检测，这种方法基于数据集群。
This neural network pattern recognition can be applied to feature extraction, clustering analysis, edge detection, signal enhancement and noise suppression, data compression, such as various links.
这样神经网络可应用于模式识别的特征提取、聚类分析、边缘检测、信号增强以及噪声抑制、数据压缩等各个环节。
Our experimental results demonstrate the performance of scene change detection based on shot is better than that of shot clustering based on multi-features.
实验表明，基于镜头的场景边界检测性能优于基于多特征的镜头聚类分析。
应用推荐