We propose a novel statistical approach to detect defects in digitized archive film by using temporal information across a number of frames modeled with an HMM. The HMM is traine...
The goal of this communication is to present a weighted likelihood discriminant for minimum error shape classification. Different from traditional Maximum Likelihood (ML) methods...
—In host-based intrusion detection systems (HIDS), anomaly detection involves monitoring for significant deviations from normal system behavior. Hidden Markov Models (HMMs) have...
Wael Khreich, Eric Granger, Robert Sabourin, Ali M...
In this paper, we propose a novel multi-dimensional distributed hidden Markov model (DHMM) framework. We first extend the theory of 2D hidden Markov models (HMMs) to arbitrary ca...
Markov statistical methods may make it possible to develop an unsupervised learning process that can automatically identify genomic structure in prokaryotes in a comprehensive way...