Abstract. Nowadays, network load is constantly increasing and high-speed infrastructures (1-10Gbps) are becoming increasingly common. In this context, flow-based intrusion detecti...
Anna Sperotto, Ramin Sadre, Pieter-Tjerk de Boer, ...
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...
Hidden Markov Models (HMMs) are increasingly being used in computer vision for applications such as: gesture analysis, action recognition from video, and illumination modeling. Th...
We present a learning algorithm for non-parametric hidden Markov models with continuous state and observation spaces. All necessary probability densities are approximated using sa...
We address the problem in signal classification applications, such as automatic speech recognition (ASR) systems that employ the hidden Markov model (HMM), that it is necessary to...