Bernhard Sick
Bernhard Sick
Professor of Intelligent Embedded Systems, University of Kassel
Verified email at - Homepage
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On-line and indirect tool wear monitoring in turning with artificial neural networks: a review of more than a decade of research
B Sick
Mechanical Systems and Signal Processing 16 (4), 487-546, 2002
Deep Learning for solar power forecasting—An approach using AutoEncoder and LSTM Neural Networks
A Gensler, J Henze, B Sick, N Raabe
2016 IEEE international conference on systems, man, and cybernetics (SMC …, 2016
Evolutionary optimization of radial basis function classifiers for data mining applications
O Buchtala, M Klimek, B Sick
Systems, Man, and Cybernetics, Part B: Cybernetics, IEEE Transactions on 35 …, 2005
Online signature verification with support vector machines based on LCSS kernel functions
C Gruber, T Gruber, S Krinninger, B Sick
IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics) 40 …, 2010
Online segmentation of time series based on polynomial least-squares approximations
E Fuchs, T Gruber, J Nitschke, B Sick
IEEE Transactions on Pattern Analysis and Machine Intelligence 32 (12), 2232 …, 2010
Engineering and mastering interwoven systems
S Tomforde, J Hähner, H Seebach, W Reif, B Sick, A Wacker, I Scholtes
ARCS 2014; 2014 Workshop Proceedings on Architecture of Computing Systems, 1-8, 2014
Online intrusion alert aggregation with generative data stream modeling
A Hofmann, B Sick
IEEE transactions on dependable and secure computing 8 (2), 282-294, 2011
Feature selection for intrusion detection: an evolutionary wrapper approach
A Hofmann, T Horeis, B Sick
2004 IEEE International Joint Conference on Neural Networks (IEEE Cat. No …, 2004
On-line motif detection in time series with SwiftMotif
E Fuchs, T Gruber, J Nitschke, B Sick
Pattern Recognition 42 (11), 3015-3031, 2009
Evolutionary optimization of radial basis function networks for intrusion detection
A Hofmann, B Sick
Proceedings of the International Joint Conference on Neural Networks, 2003 …, 2003
On the versatility of radial basis function neural networks: A case study in the field of intrusion detection
D Fisch, A Hofmann, B Sick
Information Sciences 180 (12), 2421-2439, 2010
Wave-front reconstruction with a Shack-Hartmann sensor with an iterative spline fitting method
S Groening, B Sick, K Donner, J Pfund, N Lindlein, J Schwider
Applied Optics 39 (4), 561-567, 2000
Temporal data mining using shape space representations of time series
E Fuchs, T Gruber, H Pree, B Sick
Neurocomputing 74 (1-3), 379-393, 2010
Quantitative emergence--A refined approach based on divergence measures
D Fisch, M Jänicke, B Sick, C Müller-Schloer
2010 Fourth IEEE International Conference on Self-Adaptive and Self …, 2010
Let us know your decision: pool-based active training of a generative classifier with the selection strategy 4DS
T Reitmaier, B Sick
Information Sciences 230, 106-131, 2013
Transductive active learning–A new semi-supervised learning approach based on iteratively refined generative models to capture structure in data
T Reitmaier, A Calma, B Sick
Information Sciences 293, 275-298, 2015
Trajectory prediction of cyclists using a physical model and an artificial neural network
S Zernetsch, S Kohnen, M Goldhammer, K Doll, B Sick
2016 IEEE Intelligent Vehicles Symposium (IV), 833-838, 2016
SwiftRule: Mining comprehensible classification rules for time series analysis
D Fisch, T Gruber, B Sick
IEEE Transactions on Knowledge and Data Engineering 23 (5), 774-787, 2011
Signature verification with dynamic RBF networks and time series motifs
C Gruber, M Coduro, B Sick
Tenth International Workshop on Frontiers in Handwriting Recognition, 2006
All for one or one for all? Combining heterogeneous features for activity spotting
U Blanke, B Schiele, M Kreil, P Lukowicz, B Sick, T Gruber
2010 8th IEEE International Conference on Pervasive Computing and …, 2010
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