The authors of this paper employ two (or more) autoencoders to provide a complete strategy for unsupervised non-resonant anomaly detection. Both signal extraction and data-driven background estimation can be determined with decorrelated autoencoders. method shows strong performance on test datasets has the advantage being online-compatible.

Abstract We introduce a new method for high-dimensional, online changepoint detection in settings where p-variate Gaussian data stream may undergo change mean. The procedure works by performing likelihood ratio tests against simple alternatives of different scales each coordinate, and then aggregating test statistics across coordinates. algorithm is the sense that both its storage requirements ...

Change-points in time series data are usually defined as the instants at which changes their properties occur. Detecting change-points is critical a number of applications diverse detecting credit card and insurance frauds, or intrusions into networks. Recently authors introduced an online kernel-based change-point detection method built upon direct estimation density ratio on consecutive inter...

The increasing trend of using e-versions document transmission and storage requires the electronic verification sender/author. This research presents an efficient robust online handwritten signature system targeting rates better than available state-of-the-art systems in presence skilled forgeries. Fourier analysis is employed on signatures to represent feature vectors higher dimensional space ...

In recent years due to improvements of technology within automobile industry, design process of advanced driver assistance systems for collision avoidance and traffic management has been investigated in both academics and industrial levels. Detection of traffic signs is an effective method to reach the mentioned aims. In this paper a new intelligent driver assistance system based on traffic...