Mark Jäger

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In this paper, we present an automatic classification framework combining appearance based features and hidden Markov models (HMM) to detect unusual events in image sequences. One characteristic of the classification task is that anomalies are rare. This reflects the situation in the quality control of industrial processes, where error events are scarce by(More)
Fifty healthy participants took part in a double-blind placebo-controlled study in which they were either given auditory alpha activity (8-12Hz) training (N=18), random beta training (N=12), or no training at all (N=20). A novel wireless electrode system was used for training without instructions, involving water-based electrodes mounted in an audio(More)
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