This paper presents an unsupervised segmentation method for feature sequences based on competitivelearning hidden Markov models. Models associated with the nodes of the Self-Organ...
This paper discusses biological aspects of self-organising maps (SOMs) which includes a brief review of neurophysiological findings and classical models of neurophysiological SOMs...
Thomas P. Trappenberg, Pitoyo Hartono, Douglas Ras...
This paper presents a self-organizing cognitive architecture, known as TD-FALCON, that learns to function through its interaction with the environment. TD-FALCON learns the value ...
Since the early 1990s, different infrastructures for supporting learning have been developed and practically tested in Paderborn. One of the key products of our research is the we...
Detecting abnormal behaviors in crowd scenes is quite important for public security and has been paid more and more attentions. Most previous methods use offline trained model to p...