Thomas Martinetz
Thomas Martinetz
Professor of Computer Science, University of Lübeck
Verifierad e-postadress på inb.uni-luebeck.de
Citeras av
Citeras av
'Neural-gas' network for vector quantization and its application to time-series prediction
TM Martinetz, SG Berkovich, KJ Schulten
IEEE transactions on neural networks 4 (4), 558-569, 1993
A" neural-gas" network learns topologies
T Martinetz, K Schulten
University of Illinois at Urbana-Champaign 1 (01), 1991
Neural Computation and Self-Organizing Maps; An Introduction
H Ritter, T Martinetz, K Schulten
Addison-Wesley Longman Publishing Co., Inc., 1992
Topology representing networks
T Martinetz, K Schulten
Neural Networks 7 (3), 507-522, 1994
Auditory closed-loop stimulation of the sleep slow oscillation enhances memory
HVV Ngo, T Martinetz, J Born, M Mölle
Neuron 78 (3), 545-553, 2013
Variability of eye movements when viewing dynamic natural scenes
M Dorr, T Martinetz, KR Gegenfurtner, E Barth
Journal of vision 10 (10), 28-28, 2010
Competitive Hebbian learning rule forms perfectly topology preserving maps
T Martinetz
ICANN’93: Proceedings of the International Conference on Artificial Neural …, 1993
Topology preservation in self-organizing feature maps: exact definition and measurement
T Villmann, R Der, M Herrmann, TM Martinetz
IEEE transactions on neural networks 8 (2), 256-266, 1997
Neuronale netze
H Ritter, T Martinetz, K Schulten
Munchen: Addison-Wesley, 1991
Three-dimensional neural net for learning visuomotor coordination of a robot arm
TM Martinetz, HJ Ritter, KJ Schulten
IEEE transactions on neural networks 1 (1), 131-136, 1990
Topology-conserving maps for learning visuo-motor-coordination
HJ Ritter, TM Martinetz, KJ Schulten
Neural networks 2 (3), 159-168, 1989
AFP-Pred: A random forest approach for predicting antifreeze proteins from sequence-derived properties
KK Kandaswamy, KC Chou, T Martinetz, S Möller, PN Suganthan, ...
Journal of theoretical biology 270 (1), 56-62, 2011
Driving sleep slow oscillations by auditory closed-loop stimulation—a self-limiting process
HVV Ngo, A Miedema, I Faude, T Martinetz, M Mölle, J Born
Journal of Neuroscience 35 (17), 6630-6638, 2015
Explainable COVID-19 detection using chest CT scans and deep learning
H Alshazly, C Linse, E Barth, T Martinetz
Sensors 21 (2), 455, 2021
Classifiers for ischemic stroke lesion segmentation: a comparison study
O Maier, C Schröder, ND Forkert, T Martinetz, H Handels
PloS one 10 (12), e0145118, 2015
Simple method for high-performance digit recognition based on sparse coding
K Labusch, E Barth, T Martinetz
Neural Networks, IEEE Transactions on 19 (11), 1985-1989, 2008
Deep convolutional neural networks as generic feature extractors
L Hertel, E Barth, T Käster, T Martinetz
2015 International Joint Conference on Neural Networks (IJCNN), 1-4, 2015
Dynamic fitness landscapes in molecular evolution
CO Wilke, C Ronnewinkel, T Martinetz
Physics Reports 349 (5), 395-446, 2001
Ensemble deep learning and internet of things‐based automated COVID‐19 diagnosis framework
AS Kini, AN Gopal Reddy, M Kaur, S Satheesh, J Singh, T Martinetz, ...
Contrast Media & Molecular Imaging 2022 (1), 7377502, 2022
Prediction of apoptosis protein locations with genetic algorithms and support vector machines through a new mode of pseudo amino acid composition
K Kumar Kandaswamy, G Pugalenthi, S Moller, E Hartmann, ...
Protein and Peptide Letters 17 (12), 1473-1479, 2010
Systemet kan inte utföra åtgärden just nu. Försök igen senare.
Artiklar 1–20