Thomas Martinetz

156 papers B 26C 5Misc 1Journal 61Unranked 59

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	AI-based collimation optimization for X-ray imaging using depth cameras. Neurocomputing Dominik Mairhöfer, Manuel Laufer, Lennart Berkel, Malte Sieren, Arpad Bischof, Erhardt Barth, Jörg Barkhausen, Thomas Martinetz
2026	—	`conf`	Evaluation of Time-of-flight Camera Positioning for AI-based Patient Pose Assessment in Radiography. Bildverarbeitung für die Medizin Manuel Laufer, Julius Haas, Dominik Mairhöfer, Malte Sieren, Hauke Gerdes, Fabio Leal dos Reis, Arpad Bischof, Thomas Käster, Erhardt Barth, Jörg Barkhausen, Thomas Martinetz
2026	J	`jnl`	Nearest-Neighbor Density Estimation for Dependency Suppression. CoRR Kathleen Anderson, Thomas Martinetz
2025	J	`jnl`	Do Highly Over-Parameterized Neural Networks Generalize Since Bad Solutions are Rare? IEEE Trans. Neural Networks Learn. Syst. Julius Martinetz, Thomas Martinetz
2025	J	`jnl`	Revealing Unintentional Information Leakage in Low-Dimensional Facial Portrait Representations. CoRR Kathleen Anderson, Thomas Martinetz
2025	J	`jnl`	The Resurrection of the ReLU. CoRR Cosku Can Horuz, Geoffrey Kasenbacher, Saya Higuchi, Sebastian Kairat, Jendrik Stoltz, Moritz Pesl, Bernhard Alois Moser, Christoph Linse, Thomas Martinetz, Sebastian Otte
2025	J	`jnl`	Why LLMs Cannot Think and How to Fix It. CoRR Marius Jahrens, Thomas Martinetz
2024	B	`conf`	AI-based Collimation Optimization for X-Ray Imaging using Time-of-Flight Cameras. ESANN Dominik Mairhöfer, Manuel Laufer, Lennart Berkel, Arpad Bischof, Erhardt Barth, Jörg Barkhausen, Thomas Martinetz
2024	J	`jnl`	Convolutional Neural Networks Do Work with Pre-Defined Filters. CoRR Christoph Linse, Erhardt Barth, Thomas Martinetz
2024	—	`conf`	Enhancing Generalization in Convolutional Neural Networks Through Regularization with Edge and Line Features. ICANN (1) Christoph Linse, Beatrice Brückner, Thomas Martinetz
2024	J	`jnl`	Enhancing Generalization in Convolutional Neural Networks through Regularization with Edge and Line Features. CoRR Christoph Linse, Beatrice Brückner, Thomas Martinetz
2024	B	`conf`	Leaky ReLUs That Differ in Forward and Backward Pass Facilitate Activation Maximization in Deep Neural Networks. IJCNN Christoph Linse, Erhardt Barth, Thomas Martinetz
2024	J	`jnl`	Leaky ReLUs That Differ in Forward and Backward Pass Facilitate Activation Maximization in Deep Neural Networks. CoRR Christoph Linse, Erhardt Barth, Thomas Martinetz
2024	B	`conf`	Rethinking generalization of classifiers in separable classes scenarios and over-parameterized regimes. IJCNN Julius Martinetz, Christoph Linse, Thomas Martinetz
2024	J	`jnl`	Rethinking generalization of classifiers in separable classes scenarios and over-parameterized regimes. CoRR Julius Martinetz, Christoph Linse, Thomas Martinetz
2024	—	`conf`	Revealing Unintentional Information Leakage in Low-Dimensional Facial Portrait Representations. ICANN (1) Kathleen Anderson, Thomas Martinetz
2023	B	`conf`	Convolutional Neural Networks Do Work with Pre-Defined Filters. IJCNN Christoph Linse, Erhardt Barth, Thomas Martinetz
2023	Misc	`conf`	Large Neural Networks Learning from Scratch with Very Few Data and without Explicit Regularization. ICMLC Christoph Linse, Thomas Martinetz
2023	—	`conf`	Population Coding Can Greatly Improve Performance of Neural Networks: A Comparison. ICANN (5) Marius Jahrens, Hans-Oliver Hansen, Rebecca Köhler, Thomas Martinetz
2022	J	`jnl`	A walk in the black-box: 3D visualization of large neural networks in virtual reality. Neural Comput. Appl. Christoph Linse, Hammam A. Alshazly, Thomas Martinetz
2022	J	`jnl`	Highly over-parameterized classifiers generalize since bad solutions are rare. CoRR Julius Martinetz, Thomas Martinetz
2022	J	`jnl`	Large Neural Networks Learning from Scratch with Very Few Data and without Regularization. CoRR Christoph Linse, Thomas Martinetz
2021	—	`conf`	An AI-based Framework for Diagnostic Quality Assessment of Ankle Radiographs. MIDL Dominik Mairhöfer, Manuel Laufer, Paul Martin Simon, Malte Sieren, Arpad Bischof, Thomas Käster, Erhardt Barth, Jörg Barkhausen, Thomas Martinetz
2021	J	`jnl`	COVID-Nets: deep CNN architectures for detecting COVID-19 using chest CT scans. PeerJ Comput. Sci. Hammam A. Alshazly, Christoph Linse, Mohamed Abdalla, Erhardt Barth, Thomas Martinetz
2021	J	`jnl`	Explainable COVID-19 Detection Using Chest CT Scans and Deep Learning. Sensors Hammam A. Alshazly, Christoph Linse, Erhardt Barth, Thomas Martinetz
2021	J	`jnl`	Multivariate and Online Prediction of Closing Price Using Kernel Adaptive Filtering. Comput. Intell. Neurosci. Shambhavi Mishra, Tanveer Ahmed, Vipul Kumar Mishra, Manjit Kaur, Thomas Martinetz, Amit Kumar Jain, Hammam A. Alshazly
2021	J	`jnl`	Towards Explainable Ear Recognition Systems Using Deep Residual Networks. IEEE Access Hammam A. Alshazly, Christoph Linse, Erhardt Barth, Sahar Ahmed Idris, Thomas Martinetz
2020	J	`jnl`	Deep Convolutional Neural Networks for Unconstrained Ear Recognition. IEEE Access Hammam A. Alshazly, Christoph Linse, Erhardt Barth, Thomas Martinetz
2020	J	`jnl`	Explainable COVID-19 Detection Using Chest CT Scans and Deep Learning. CoRR Hammam A. Alshazly, Christoph Linse, Erhardt Barth, Thomas Martinetz
2020	J	`jnl`	Feature Products Yield Efficient Networks. CoRR Philipp Grüning, Thomas Martinetz, Erhardt Barth
2020	—	`conf`	Log-Nets: Logarithmic Feature-Product Layers Yield More Compact Networks. ICANN (2) Philipp Grüning, Thomas Martinetz, Erhardt Barth
2020	B	`conf`	Solving Raven's Progressive Matrices with Multi-Layer Relation Networks. IJCNN Marius Jahrens, Thomas Martinetz
2020	J	`jnl`	Solving Raven's Progressive Matrices with Multi-Layer Relation Networks. CoRR Marius Jahrens, Thomas Martinetz
2019	J	`jnl`	Ensembles of Deep Learning Models and Transfer Learning for Ear Recognition. Sensors Hammam A. Alshazly, Christoph Linse, Erhardt Barth, Thomas Martinetz
2019	J	`jnl`	Handcrafted versus CNN Features for Ear Recognition. Symmetry Hammam A. Alshazly, Christoph Linse, Erhardt Barth, Thomas Martinetz
2019	—	`conf`	Multi-layer relation networks for relational reasoning. APPIS Marius Jahrens, Thomas Martinetz
2018	J	`jnl`	Multi-layer Relation Networks. CoRR Marius Jahrens, Thomas Martinetz
2017	J	`jnl`	Deep Convolutional Neural Networks as Generic Feature Extractors. CoRR Lars Hertel, Erhardt Barth, Thomas Käster, Thomas Martinetz
2017	B	`conf`	Perception space analysis: From color vision to odor perception. IJCNN Amir Madany Mamlouk, Martin Haker, Thomas Martinetz
2017	B	`conf`	Recursive autoconvolution for unsupervised learning of convolutional neural networks. IJCNN Boris Knyazev, Erhardt Barth, Thomas Martinetz
2017	B	`conf`	Sensing Forest for Pattern Recognition. ACIVS Irina Burciu, Thomas Martinetz, Erhardt Barth
2016	J	`jnl`	A Thalamocortical Neural Mass Model of the EEG during NREM Sleep and Its Response to Auditory Stimulation. PLoS Comput. Biol. Michael Schellenberger Costa, Arne Weigenand, Hong-Viet Victor Ngo, Lisa Marshall, Jan Born, Thomas Martinetz, Jens Christian Claussen
2016	J	`jnl`	Autoconvolution for Unsupervised Feature Learning. CoRR Boris Knyazev, Erhardt Barth, Thomas Martinetz
2016	—	`conf`	Hierarchical Manifold Sensing with Foveation and Adaptive Partitioning of the Dataset. HVEI Irina Burciu, Thomas Martinetz, Erhardt Barth
2016	J	`jnl`	Learning Efficient Data Representations With Orthogonal Sparse Coding. IEEE Trans. Computational Imaging Henry Schütze, Erhardt Barth, Thomas Martinetz
2016	J	`jnl`	Modeling the effect of sleep regulation on a neural mass model. J. Comput. Neurosci. Michael Schellenberger Costa, Jan Born, Jens Christian Claussen, Thomas Martinetz
2015	B	`conf`	Deep convolutional neural networks as generic feature extractors. IJCNN Lars Hertel, Erhardt Barth, Thomas Käster, Thomas Martinetz
2015	—	`conf`	Foveated Manifold Sensing for object recognition. BlackSeaCom Irina Burciu, Thomas Martinetz, Erhardt Barth
2015	B	`conf`	Learning orthogonal sparse representations by using geodesic flow optimization. IJCNN Henry Schütze, Erhardt Barth, Thomas Martinetz
2015	J	`jnl`	Maximum distance minimization for feature weighting. Pattern Recognit. Lett. Jens Hocke, Thomas Martinetz
2015	J	`jnl`	Self-organizing maps for hand and full body tracking. Neurocomputing Foti Coleca, Andreea State, Sascha Klement, Erhardt Barth, Thomas Martinetz
2014	—	`conf`	An adaptive hierarchical sensing scheme for sparse signals. Human Vision and Electronic Imaging Henry Schütze, Erhardt Barth, Thomas Martinetz
2014	J	`jnl`	Characterization of K-Complexes and Slow Wave Activity in a Neural Mass Model. PLoS Comput. Biol. Arne Weigenand, Michael Schellenberger Costa, Hong-Viet Victor Ngo, Jens Christian Claussen, Thomas Martinetz
2014	J	`jnl`	Committees of deep feedforward networks trained with few data. CoRR Bogdan Miclut, Thomas Käster, Thomas Martinetz, Erhardt Barth
2014	C	`conf`	Global Metric Learning by Gradient Descent. ICANN Jens Hocke, Thomas Martinetz
2014	—	`conf`	Key-point Detection with Multi-layer Center-surround Inhibition. VISAPP (1) Foti Coleca, Sabrina Zîrnovean, Thomas Käster, Thomas Martinetz, Erhardt Barth
2014	B	`conf`	Learning and modeling big data. ESANN Barbara Hammer, Haibo He, Thomas Martinetz
2014	—	`conf`	Visual manifold sensing. Human Vision and Electronic Imaging Irina Burciu, Adrian Ion-Margineanu, Thomas Martinetz, Erhardt Barth
2013	C	`conf`	Feature Weighting by Maximum Distance Minimization. ICANN Jens Hocke, Thomas Martinetz
2013	—	`conf`	Gesture Interfaces with Depth Sensors. Time-of-Flight and Depth Imaging Foti Coleca, Thomas Martinetz, Erhardt Barth
2013	—	`conf`	Optimizing depth-of-field based on a range map and a wavelet transform. Multimedia Content and Mobile Devices Mike Wellner, Thomas Käster, Thomas Martinetz, Erhardt Barth
2013	—	`conf`	Real-time skeleton tracking for embedded systems. Multimedia Content and Mobile Devices Foti Coleca, Sascha Klement, Thomas Martinetz, Erhardt Barth
2013	J	`jnl`	The Support Feature Machine: Classification with the Least Number of Features and Application to Neuroimaging Data. Neural Comput. Sascha Klement, Silke Anders, Thomas Martinetz
2012	—	`conf`	A Multivariate Approach to Estimate Complexity of FMRI Time Series. ICANN (2) Henry Schütze, Thomas Martinetz, Silke Anders, Amir Madany Mamlouk
2012	—	`conf`	Application of non-linear transform coding to image processing. Human Vision and Electronic Imaging Jens Hocke, Erhardt Barth, Thomas Martinetz
2012	—	`conf`	Hand Tracking with an Extended Self-Organizing Map. WSOM Andreea State, Foti Coleca, Erhardt Barth, Thomas Martinetz
2012	—	`conf`	How to make a small phone camera shoot like a big DSLR: creating and fusing multi-modal exposure series. Human Vision and Electronic Imaging Thomas Binder, Florian Kriener, Christian Wichner, Manuel Wille, Mike Wellner, Thomas Käster, Thomas Martinetz, Erhardt Barth
2012	J	`jnl`	Intrinsic Dimensionality Predicts the Saliency of Natural Dynamic Scenes. IEEE Trans. Pattern Anal. Mach. Intell. Eleonora Vig, Michael Dorr, Thomas Martinetz, Erhardt Barth
2012	J	`jnl`	On the boundedness of an Iteration involving Points on the Hypersphere. Int. J. Comput. Geom. Appl. Thomas Binder, Thomas Martinetz
2012	—	`conf`	Sparse Coding Neural Gas Applied to Image Recognition. WSOM Horia Coman, Erhardt Barth, Thomas Martinetz
2012	J	`jnl`	Sparse Coding and Selected Applications. Künstliche Intell. Jens Hocke, Kai Labusch, Erhardt Barth, Thomas Martinetz
2011	J	`jnl`	Advances in artificial neural networks, machine learning, and computational intelligence. Neurocomputing John Aldo Lee, Frank-Michael Schleif, Thomas Martinetz
2011	J	`jnl`	BLProt: Prediction of bioluminescent proteins based on Support Vector Machine and ReliefF feature selection. BMC Bioinform. Krishna Kumar Kandaswamy, Ganesan Pugalenthi, Mehrnaz Khodam Hazrati, Kai-Uwe Kalies, Thomas Martinetz
2011	J	`jnl`	Eye Movements Show Optimal Average Anticipation with Natural Dynamic Scenes. Cogn. Comput. Eleonora Vig, Michael Dorr, Thomas Martinetz, Erhardt Barth
2011	—	`conf`	On the Problem of Finding the Least Number of Features by L1-Norm Minimisation. ICANN (1) Sascha Klement, Thomas Martinetz
2011	J	`jnl`	PhyloMap: an algorithm for visualizing relationships of large sequence data sets and its application to the influenza A virus genome. BMC Bioinform. Jiajie Zhang, Amir Madany Mamlouk, Thomas Martinetz, Suhua Chang, Jing Wang, Rolf Hilgenfeld
2011	J	`jnl`	Robust and Fast Learning of Sparse Codes With Stochastic Gradient Descent. IEEE J. Sel. Top. Signal Process. Kai Labusch, Erhardt Barth, Thomas Martinetz
2011	J	`jnl`	Soft-competitive learning of sparse codes and its application to image reconstruction. Neurocomputing Kai Labusch, Erhardt Barth, Thomas Martinetz
2010	—	`conf`	A Learned Saliency Predictor for Dynamic Natural Scenes. ICANN (3) Eleonora Vig, Michael Dorr, Thomas Martinetz, Erhardt Barth
2010	C	`conf`	A New Approach to Classification with the Least Number of Features. ICMLA Sascha Klement, Thomas Martinetz
2010	—	`conf`	Bag of Pursuits and Neural Gas for Improved Sparse Coding. COMPSTAT Kai Labusch, Erhardt Barth, Thomas Martinetz
2010	B	`conf`	Learning sparse codes for image reconstruction. ESANN Kai Labusch, Thomas Martinetz
2010	J	`jnl`	On the boundedness of an iteration involving points on the hypersphere CoRR Thomas Binder, Thomas Martinetz
2010	J	`jnl`	Shading constraint improves accuracy of time-of-flight measurements. Comput. Vis. Image Underst. Martin Böhme, Martin Haker, Thomas Martinetz, Erhardt Barth
2010	B	`conf`	Statistical Fourier Descriptors for Defect Image Classification. ICPR Fabian Timm, Thomas Martinetz
2010	—	`conf`	The Support Feature Machine for Classifying with the Least Number of Features. ICANN (2) Sascha Klement, Thomas Martinetz
2009	J	`jnl`	Adaptive Dynamics of Regulatory Networks: Size Matters. EURASIP J. Bioinform. Syst. Biol. Dirk Repsilber, Thomas Martinetz, Mats Björklund
2009	—	`conf`	Approaching the Time Dependent Cocktail Party Problem with Online Sparse Coding Neural Gas. WSOM Kai Labusch, Erhardt Barth, Thomas Martinetz
2009	—	`conf`	Deictic Gestures with a Time-of-Flight Camera. Gesture Workshop Martin Haker, Martin Böhme, Thomas Martinetz, Erhardt Barth
2009	—	`conf`	Face Detection Using a Time-of-Flight Camera. Dyn3D Martin Böhme, Martin Haker, Kolja Riemer, Thomas Martinetz, Erhardt Barth
2009	—	`conf`	Multimodal Sparse Features for Object Detection. ICANN (2) Martin Haker, Thomas Martinetz, Erhardt Barth
2009	—	`conf`	Optical Inspection of Welding Seams. VISIGRAPP (Selected Papers) Fabian Timm, Thomas Martinetz, Erhardt Barth
2009	—	`conf`	Self-Organizing Maps for Pose Estimation with a Time-of-Flight Camera. Dyn3D Martin Haker, Martin Böhme, Thomas Martinetz, Erhardt Barth
2009	J	`jnl`	SoftDoubleMaxMinOver: Perceptron-Like Training of Support Vector Machines. IEEE Trans. Neural Networks Thomas Martinetz, Kai Labusch, Daniel Schneegaß
2009	J	`jnl`	Sparse Coding Neural Gas: Learning of overcomplete data representations. Neurocomputing Kai Labusch, Erhardt Barth, Thomas Martinetz
2009	—	`conf`	Welding Inspection using Novel Specularity Features and a One-class SVM. VISAPP (1) Fabian Timm, Sascha Klement, Thomas Martinetz, Erhardt Barth
2008	J	`jnl`	A facial feature tracker for human-computer interaction based on 3D Time-Of-Flight cameras. Int. J. Intell. Syst. Technol. Appl. Martin Böhme, Martin Haker, Thomas Martinetz, Erhardt Barth
2008	B	`conf`	A software framework for simulating eye trackers. ETRA Martin Böhme, Michael Dorr, Mathis Graw, Thomas Martinetz, Erhardt Barth
2008	B	`conf`	Fast model selection for MaxMinOver-based training of support vector machines. ICPR Fabian Timm, Sascha Klement, Thomas Martinetz
2008	B	`conf`	Learning Data Representations with Sparse Coding Neural Gas. ESANN Kai Labusch, Erhardt Barth, Thomas Martinetz
2008	—	`conf`	Reliability of Cross-Validation for SVMs in High-Dimensional, Low Sample Size Scenarios. ICANN (1) Sascha Klement, Amir Madany Mamlouk, Thomas Martinetz
2008	—	`conf`	Scale-invariant range features for time-of-flight camera applications. CVPR Workshops Martin Haker, Martin Böhme, Thomas Martinetz, Erhardt Barth
2008	—	`conf`	Shading constraint improves accuracy of time-of-flight measurements. CVPR Workshops Martin Böhme, Martin Haker, Thomas Martinetz, Erhardt Barth
2008	—	`conf`	Simple Incremental One-Class Support Vector Classification. DAGM-Symposium Kai Labusch, Fabian Timm, Thomas Martinetz
2008	J	`jnl`	Simple Method for High-Performance Digit Recognition Based on Sparse Coding. IEEE Trans. Neural Networks Kai Labusch, Erhardt Barth, Thomas Martinetz
2008	—	`conf`	Sparse Coding Neural Gas for the Separation of Noisy Overcomplete Sources. ICANN (1) Kai Labusch, Erhardt Barth, Thomas Martinetz
2008	B	`conf`	Uncertainty propagation for quality assurance in Reinforcement Learning. IJCNN Daniel Schneegaß, Steffen Udluft, Thomas Martinetz
2007	B	`conf`	Explicit Kernel Rewards Regression for data-efficient near-optimal policy identification. ESANN Daniel Schneegaß, Steffen Udluft, Thomas Martinetz
2007	—	`conf`	Improving Optimality of Neural Rewards Regression for Data-Efficient Batch Near-Optimal Policy Identification. ICANN (1) Daniel Schneegaß, Steffen Udluft, Thomas Martinetz
2007	—	`conf`	Learning optimal features for visual pattern recognition. Human Vision and Electronic Imaging Kai Labusch, Udo Siewert, Thomas Martinetz, Erhardt Barth
2007	B	`conf`	Neural Rewards Regression for near-optimal policy identification in Markovian and partial observable environments. ESANN Daniel Schneegaß, Steffen Udluft, Thomas Martinetz
2007	B	`conf`	The Intrinsic Recurrent Support Vector Machine. ESANN Daniel Schneegaß, Anton Maximilian Schäfer, Thomas Martinetz
2006	—	`conf`	A Single-Camera Remote Eye Tracker. PIT André Meyer, Martin Böhme, Thomas Martinetz, Erhardt Barth
2006	J	`jnl`	Eye movement predictions on natural videos. Neurocomputing Martin Böhme, Michael Dorr, Christopher Krause, Thomas Martinetz, Erhardt Barth
2006	—	`conf`	Fast and Easy Computation of Approximate Smallest Enclosing Balls. SIBGRAPI Thomas Martinetz, Amir Madany Mamlouk, Cicero Mota
2006	—	`conf`	Gaze-Contingent Spatio-temporal Filtering in a Head-Mounted Display. PIT Michael Dorr, Martin Böhme, Thomas Martinetz, Erhardt Barth
2006	B	`conf`	Gaze-contingent temporal filtering of video. ETRA Martin Böhme, Michael Dorr, Thomas Martinetz, Erhardt Barth
2006	—	`conf`	Guiding Eye Movements for Better Communication and Augmented Vision. PIT Erhardt Barth, Michael Dorr, Martin Böhme, Karl R. Gegenfurtner, Thomas Martinetz
2006	—	`conf`	Guiding the mind's eye: improving communication and vision by external control of the scanpath. Human Vision and Electronic Imaging Erhardt Barth, Michael Dorr, Martin Böhme, Karl R. Gegenfurtner, Thomas Martinetz
2006	—	`conf`	Kernel Rewards Regression: An Information Efficient Batch Policy Iteration Approach. Artificial Intelligence and Applications Daniel Schneegaß, Steffen Udluft, Thomas Martinetz
2006	—	`conf`	MaxMinOver Regression: A Simple Incremental Approach for Support Vector Function Approximation. ICANN (1) Daniel Schneegaß, Kai Labusch, Thomas Martinetz
2006	B	`conf`	OnlineDoubleMaxMinOver: a simple approximate time and information efficient online Support Vector Classification method. ESANN Daniel Schneegaß, Thomas Martinetz, Michael Clausohm
2005	—	`ed.`	18th International Conference on Architecture of Computing Systems, Workshops, Innsbruck, Austria, March 2005 ARCS Workshops Uwe Brinkschulte, Jürgen Becker, Dietmar Fey, Christian Hochberger, Thomas Martinetz, Christian Müller-Schloer, Hartmut Schmeck, Theo Ungerer, Rolf P. Würtz
2005	J	`jnl`	Medical image compression using topology-preserving neural networks. Eng. Appl. Artif. Intell. Anke Meyer-Bäse, Karsten Jancke, Axel Wismüller, Simon Foo, Thomas Martinetz
2005	—	`conf`	SoftDoubleMinOver: A Simple Procedure for Maximum Margin Classification. ICANN (2) Thomas Martinetz, Kai Labusch, Daniel Schneegaß
2005	J	`jnl`	Unsupervised spike sorting with ICA and its evaluation using GENESIS simulations. Neurocomputing Amir Madany Mamlouk, Hannah Sharp, Kerstin M. L. Menne, Ulrich G. Hofmann, Thomas Martinetz
2005	—	`conf`	Visibility of temporal blur on a gaze-contingent display. APGV Michael Dorr, Thomas Martinetz, Martin Böhme, Erhardt Barth
2004	J	`jnl`	Binding Matrix: a Novel Approach for Binding Site Recognition. J. Bioinform. Comput. Biol. Jan T. Kim, Jan E. Gewehr, Thomas Martinetz
2004	B	`conf`	MaxMinOver: a simple incremental learning procedure for support vector classification. IJCNN Thomas Martinetz
2004	—	`conf`	MinOver Revisited for Incremental Support-Vector-Classification. DAGM-Symposium Thomas Martinetz
2004	J	`jnl`	On the dimensions of the olfactory perception space. Neurocomputing Amir Madany Mamlouk, Thomas Martinetz
2004	—	`conf`	Saliency Extraction for Gaze-Contingent Displays. GI Jahrestagung (2) Martin Böhme, Christopher Krause, Thomas Martinetz, Erhardt Barth
2003	—	`conf`	Dynamic predictions of tracked gaze. ISSPA (1) Erhardt Barth, Jan Drewes, Thomas Martinetz
2003	—	`conf`	Individual predictions of eye-movements with dynamic scenes. Human Vision and Electronic Imaging Erhardt Barth, Jan Drewes, Thomas Martinetz
2003	B	`conf`	Model-Free Functional MRI Analysis Using Topographic Independent Component Analysis. ESANN Anke Meyer-Bäse, Thomas D. Otto, Thomas Martinetz, Dorothee Auer, Axel Wismüller
2003	—	`conf`	One-Class Classification with Subgaussians. DAGM-Symposium Amir Madany Mamlouk, Jan T. Kim, Erhardt Barth, Michael Brauckmann, Thomas Martinetz
2003	B	`conf`	Statistical learning for detecting protein-DNA-binding sites. IJCNN Thomas Martinetz, Jan E. Gewehr, Jan T. Kim
2001	C	`conf`	A Method for Incorporation of New Evidence to Improve World State Estimation. RoboCup Martin Haker, André Meyer, Daniel Polani, Thomas Martinetz
2001	—	`conf`	An Information-Theoretic Approach for the Quantification of Relevance. ECAL Daniel Polani, Thomas Martinetz, Jan T. Kim
2001	—	`conf`	On the Effects of Transcription Factor Properties on the Information Content of Binding Sites. German Conference on Bioinformatics Jan T. Kim, Thomas Martinetz, Daniel Polani
2000	C	`conf`	Team Description for Lucky Lübeck - Evidence-Based World State Estimation. RoboCup Daniel Polani, Thomas Martinetz
1999	J	`jnl`	Genetic Algorithms in Time-Dependent Environments CoRR Christopher Ronnewinkel, Claus O. Wilke, Thomas Martinetz
1999	—	`conf`	Molecular Evolution in Time-Dependent Environments. ECAL Claus O. Wilke, Christopher Ronnewinkel, Thomas Martinetz
1997	J	`jnl`	Topology preservation in self-organizing feature maps: exact definition and measurement. IEEE Trans. Neural Networks Thomas Villmann, Ralf Der, J. Michael Herrmann, Thomas Martinetz
1995	—	`conf`	Neural Network Control for Steel Rolling Mills. SNN Symposium on Neural Networks Thomas Martinetz, Peter Protzel, Otto Gramckow, Günter Sörgel
1994	—	`conf`	Topology Preservation in Self-Organizing Feature Maps: General Definition and Efficient Measurement. Fuzzy Days Thomas Villmann, Ralf Der, J. Michael Herrmann, Thomas Martinetz
1994	J	`jnl`	Topology representing networks. Neural Networks Thomas Martinetz, Klaus Schulten
1993	J	`jnl`	'Neural-gas' network for vector quantization and its application to time-series prediction. IEEE Trans. Neural Networks Thomas Martinetz, Stanislav G. Berkovich, Klaus Schulten
1993	—	`conf`	A neural network with Hebbian-like adaptation rules learning visuomotor coordination of a PUMA robot. ICNN Thomas Martinetz, Klaus Schulten
1992	—	`book`	Neural computation and self-organizing maps - an introduction. Helge J. Ritter, Thomas Martinetz, Klaus Schulten
1992	—	`—`	Selbstorganisierende neuronale Netzwerkmodelle zur Bewegungssteuerung. Thomas Martinetz
1991	—	`book`	Neuronale Netze - eine Einführung in die Neuroinformatik selbstorganisierter Netzwerke (2. Aufl.). Helge J. Ritter, Thomas Martinetz, Klaus Schulten
1991	—	`conf`	Vector Quantization Algorithm for Time Series Prediction and Visuo-Motor Control of Robots. Wissensbasierte Systeme Stan Berkovitch, Philippe Dalger, Ted Hesselroth, Thomas Martinetz, Benoît Noël, Jörg A. Walter, Klaus Schulten
1990	B	`conf`	Hierarchical neural net for learning control of a robot's arm and gripper. IJCNN Thomas Martinetz, Klaus Schulten
1990	J	`jnl`	Three-dimensional neural net for learning visuomotor coordination of a robot arm. IEEE Trans. Neural Networks Thomas Martinetz, Helge J. Ritter, Klaus Schulten
1989	J	`jnl`	Topology-conserving maps for learning visuo-motor-coordination. Neural Networks Helge J. Ritter, Thomas Martinetz, Klaus Schulten