Thomas Martinetz

Thomas Martinetz, Steffen Udluft, Daniel Schneegaß, 2008, 2008 IEEE International Joint Conference on Neural Networks (IEEE World Congress on Computational Intelligence).

SoftDoubleMinOver: A Simple Procedure for Maximum Margin Classification

Thomas Martinetz, Kai Labusch, Daniel Schneegaß, 2005, ICANN.

Multi-layer Relation Networks pdf

Thomas Martinetz, Marius Jahrens, 2018, ArXiv.

Team Description for Lucky Lübeck - Evidence-Based World State Estimation

Thomas Martinetz, Daniel Polani, D. Polani, 2000, RoboCup.

Improving Optimality of Neural Rewards Regression for Data-Efficient Batch Near-Optimal Policy Identification

Thomas Martinetz, Steffen Udluft, Daniel Schneegaß, 2007, ICANN.

Recursive autoconvolution for unsupervised learning of convolutional neural networks

Thomas Martinetz, Erhardt Barth, Boris Knyazev, 2016, 2017 International Joint Conference on Neural Networks (IJCNN).

Learning optimal features for visual pattern recognition

Thomas Martinetz, Erhardt Barth, Kai Labusch, 2007, Electronic Imaging.

Gesture Interfaces with Depth Sensors

Thomas Martinetz, Erhardt Barth, Foti Coleca, 2013, Time-of-Flight and Depth Imaging.

Fast and Easy Computation of Approximate Smallest Enclosing Balls

Thomas Martinetz, Cicero Mota, Amir Madany Mamlouk, 2006, 2006 19th Brazilian Symposium on Computer Graphics and Image Processing.

Model-Free Functional MRI Analysis Using Topographic Independent Component Analysis

Thomas Martinetz, Anke Meyer-Bäse, Dorothee P. Auer, 2004, ESANN.

Bag of Pursuits and Neural Gas for Improved Sparse Coding

Thomas Martinetz, Erhardt Barth, Kai Labusch, 2010, COMPSTAT.

Gaze-contingent temporal filtering of video

Thomas Martinetz, Erhardt Barth, Martin Böhme, 2006, ETRA '06.

Statistical Fourier Descriptors for Defect Image Classification

Thomas Martinetz, Fabian Timm, 2010, 2010 20th International Conference on Pattern Recognition.

On the Problem of Finding the Least Number of Features by L1-Norm Minimisation

Thomas Martinetz, Sascha Klement, T. Martinetz, 2011, ICANN.

Medical image compression using topology-preserving neural networks

Thomas Martinetz, Anke Meyer-Bäse, Axel Wismüller, 2005, Eng. Appl. Artif. Intell..

Visibility of temporal blur on a gaze-contingent display

Thomas Martinetz, Erhardt Barth, Martin Böhme, 2005, APGV '05.

One-Class Classification with Subgaussians

Thomas Martinetz, Erhardt Barth, Amir Madany Mamlouk, 2003, DAGM-Symposium.

Guidance of eye movements on a gaze-contingent display

Thomas Martinetz, Karl R. Gegenfurtner, Michael Dorr, 2004 .

Using coarse-grained, discrete systems for data-driven inference of regulatory gene networks : Perspectives and limitations for reverse engineering

Thomas Martinetz, Jan T. Kim, Hans Liljenström, 2002 .

Explicit Kernel Rewards Regression for data-efficient near-optimal policy identification

Thomas Martinetz, Steffen Udluft, Daniel Schneegaß, 2007, ESANN.

Deep convolutional neural networks as generic feature extractors

Thomas Martinetz, Lars Hertel, Erhardt Barth, 2015, 2015 International Joint Conference on Neural Networks (IJCNN).

Multimodal Sparse Features for Object Detection

Thomas Martinetz, Erhardt Barth, Martin Haker, 2009, ICANN.

Statistical learning for detecting protein-DNA-binding sites

Thomas Martinetz, Jan T. Kim, Jan E. Gewehr, 2003, Proceedings of the International Joint Conference on Neural Networks, 2003..

On the Effects of Transcription Factor Properties on the Information Content of Binding Sites

Thomas Martinetz, Daniel Polani, Jan T. Kim, 2001, German Conference on Bioinformatics.

Stimulation Augments Spike Sequence Replay and Memory Consolidation during Slow-Wave Sleep

Thomas Martinetz, Maxim Bazhenov, Yina Wei, 2019, The Journal of Neuroscience.

How to make a small phone camera shoot like a big DSLR: creating and fusing multi-modal exposure series

Thomas Martinetz, Erhardt Barth, Thomas Binder, 2012, Electronic Imaging.

Kernel Rewards Regression: An Information Efficient Batch Policy Iteration Approach

Thomas Martinetz, Steffen Udluft, Daniel Schneegaß, 2006, Artificial Intelligence and Applications.

Variability of eye movements when viewing dynamic natural scenes.

Thomas Martinetz, Karl R Gegenfurtner, Michael Dorr, 2010, Journal of vision.

Maximum distance minimization for feature weighting

Thomas Martinetz, Jens Hocke, T. Martinetz, 2015, Pattern Recognit. Lett..

A Multivariate Approach to Estimate Complexity of FMRI Time Series

Thomas Martinetz, Amir Madany Mamlouk, Henry Schütze, 2012, ICANN.

Optical Inspection of Welding Seams

Thomas Martinetz, Erhardt Barth, Fabian Timm, 2009, VISIGRAPP.

'Neural-gas' network for vector quantization and its application to time-series prediction

Thomas Martinetz, Klaus Schulten, Stanislav G. Berkovich, 1993, IEEE Trans. Neural Networks.

KI-SIGS: Artificial Intelligence for the Northern German Health Ecosystem

Thomas Martinetz, Christoph Lüth, Dirk Nowotka, 2020 .

Modeling the effect of sleep regulation on a neural mass model

Thomas Martinetz, Jens Christian Claussen, Jan Born, 2016, Journal of Computational Neuroscience.

Three-dimensional neural net for learning visuomotor coordination of a robot arm

Helge J. Ritter, Thomas Martinetz, Klaus Schulten, 1990, IEEE Trans. Neural Networks.

A New Approach to Classification with the Least Number of Features

Thomas Martinetz, Sascha Klement, T. Martinetz, 2010, 2010 Ninth International Conference on Machine Learning and Applications.

Learning Data Representations with Sparse Coding Neural Gas

Thomas Martinetz, Erhardt Barth, Kai Labusch, 2008, ESANN.

Deictic Gestures with a Time-of-Flight Camera

Thomas Martinetz, Erhardt Barth, Martin Böhme, 2009, Gesture Workshop.

Solving Raven’s Progressive Matrices with Multi-Layer Relation Networks

Thomas Martinetz, Marius Jahrens, T. Martinetz, 2020, 2020 International Joint Conference on Neural Networks (IJCNN).

The Support Feature Machine for Classifying with the Least Number of Features

Thomas Martinetz, Sascha Klement, 2010, ICANN.

Selbstorganisierende neuronale Netzwerkmodelle zur Bewegungssteuerung

Thomas Martinetz, 1992, DISKI.

An Information-Theoretic Approach for the Quantification of Relevance

Thomas Martinetz, Daniel Polani, Jan T. Kim, 2001, ECAL.

A neural network with Hebbian-like adaptation rules learning visuomotor coordination of a PUMA robot

Thomas Martinetz, Klaus Schulten, 1993, IEEE International Conference on Neural Networks.

On the boundedness of an Iteration involving Points on the Hypersphere

Thomas Martinetz, Thomas Binder, 2012, Int. J. Comput. Geom. Appl..

Explainable COVID-19 Detection Using Chest CT Scans and Deep Learning

Thomas Martinetz, Erhardt Barth, Hammam Alshazly, 2021, Sensors.

An AI-based Framework for Diagnostic Quality Assessment of Ankle Radiographs

Thomas Martinetz, Erhardt Barth, Arpad Bischof, 2021, MIDL.

Towards Explainable Ear Recognition Systems Using Deep Residual Networks

Thomas Martinetz, Erhardt Barth, Hammam Alshazly, 2021, IEEE Access.

EYE MOVEMENT PREDICTIONS ENHANCED BY SACCADE DETECTION

Thomas Martinetz, Erhardt Barth, Martin Böhme, 2004 .

Driving Sleep Slow Oscillations by Auditory Closed-Loop Stimulation—A Self-Limiting Process

Thomas Martinetz, Jan Born, Matthias Mölle, 2015, The Journal of Neuroscience.

Prediction of apoptosis protein locations with genetic algorithms and support vector machines through a new mode of pseudo amino acid composition.

Thomas Martinetz, Ganesan Pugalenthi, P N Suganthan, 2010, Protein and peptide letters.

A facial feature tracker for human-computer interaction based on 3D TOF cameras

Thomas Martinetz, Erhardt Barth, Martin Böhme, 2009 .

EcmPred: prediction of extracellular matrix proteins based on random forest with maximum relevance minimum redundancy feature selection.

Thomas Martinetz, Ganesan Pugalenthi, Krishna Kumar Kandaswamy, 2013, Journal of theoretical biology.