34 citations · 46 across the 3 of their papers we have counts for
6 papers
Self-Adaptation of Activity Recognition Systems to New Sensors
David Bannach, Martin Jänicke, Vitor F. Rey +3
Traditional activity recognition systems work on the basis of training, taking a fixed set of sensors into account. In this article, we focus on the question how pattern recognitio…
Organic Computing in the Spotlight
Sven Tomforde, Bernhard Sick, Christian Müller-Schloer
Organic Computing is an initiative in the field of systems engineering that proposed to make use of concepts such as self-adaptation and self-organisation to increase the robustnes…
Variational Bayesian Inference for Hidden Markov Models With Multivariate Gaussian Output Distributions
Christian Gruhl, Bernhard Sick
Hidden Markov Models (HMM) have been used for several years in many time series analysis or pattern recognitions tasks. HMM are often trained by means of the Baum-Welch algorithm w…
Towards Automation of Knowledge Understanding: An Approach for Probabilistic Generative Classifiers
Dominik Fisch, Christian Gruhl, Edgar Kalkowski +2
After data selection, pre-processing, transformation, and feature extraction, knowledge extraction is not the final step in a data mining process. It is then necessary to understan…
Detecting Novel Processes with CANDIES -- An Holistic Novelty Detection Technique based on Probabilistic Models
Christian Gruhl, Bernhard Sick
In this article, we propose CANDIES (Combined Approach for Novelty Detection in Intelligent Embedded Systems), a new approach to novelty detection in technical systems. We assume t…
The Responsibility Weighted Mahalanobis Kernel for Semi-Supervised Training of Support Vector Machines for Classification
Tobias Reitmaier, Bernhard Sick
Kernel functions in support vector machines (SVM) are needed to assess the similarity of input samples in order to classify these samples, for instance. Besides standard kernels su…