| Year |
Citation |
Score |
| 2016 |
Burciu I, Martinetz T, Barth E. Hierarchical manifold sensing with foveation and adaptive partitioning of the dataset Journal of Imaging Science and Technology. 60. DOI: 10.2352/J.ImagingSci.Technol.2016.60.2.020402 |
1 |
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| 2015 |
Maier O, Schröder C, Forkert ND, Martinetz T, Handels H. Classifiers for Ischemic Stroke Lesion Segmentation: A Comparison Study. Plos One. 10: e0145118. PMID 26672989 DOI: 10.1371/journal.pone.0145118 |
1 |
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| 2015 |
Dornseifer S, Willkomm S, Far RK, Liebschwager J, Beltsiou F, Frank K, Laufer SD, Martinetz T, Sczakiel G, Claussen JC, Restle T. RNAi revised - target mRNA-dependent enhancement of gene silencing. Nucleic Acids Research. PMID 26578554 DOI: 10.1093/nar/gkv1200 |
1 |
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| 2015 |
Ngo HV, Miedema A, Faude I, Martinetz T, Mölle M, Born J. Driving sleep slow oscillations by auditory closed-loop stimulation-a self-limiting process. The Journal of Neuroscience : the Official Journal of the Society For Neuroscience. 35: 6630-8. PMID 25926443 DOI: 10.1523/JNEUROSCI.3133-14.2015 |
1 |
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| 2015 |
Krause C, Ens K, Fechner K, Voigt J, Fraune J, Rohwäder E, Hahn M, Danckwardt M, Feirer C, Barth E, Martinetz T, Stöcker W. EUROPattern Suite technology for computer-aided immunofluorescence microscopy in autoantibody diagnostics. Lupus. 24: 516-29. PMID 25801895 DOI: 10.1177/0961203314559635 |
1 |
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| 2015 |
Hertel L, Barth E, Kaster T, Martinetz T. Deep convolutional neural networks as generic feature extractors Proceedings of the International Joint Conference On Neural Networks. 2015. DOI: 10.1109/IJCNN.2015.7280683 |
1 |
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| 2015 |
Schütze H, Barth E, Martinetz T. Learning orthogonal sparse representations by using geodesic flow optimization Proceedings of the International Joint Conference On Neural Networks. 2015. DOI: 10.1109/IJCNN.2015.7280651 |
1 |
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| 2015 |
Burciu I, Martinetz T, Barth E. Foveated Manifold Sensing for object recognition 2015 Ieee International Black Sea Conference On Communications and Networking, Blackseacom 2015. 196-200. DOI: 10.1109/BlackSeaCom.2015.7185114 |
1 |
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| 2015 |
Coleca F, State A, Klement S, Barth E, Martinetz T. Self-organizing maps for hand and full body tracking Neurocomputing. 147: 174-184. DOI: 10.1016/j.neucom.2013.10.041 |
1 |
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| 2014 |
Weigenand A, Schellenberger Costa M, Ngo HV, Claussen JC, Martinetz T. Characterization of K-complexes and slow wave activity in a neural mass model. Plos Computational Biology. 10: e1003923. PMID 25392991 DOI: 10.1371/journal.pcbi.1003923 |
1 |
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| 2014 |
Schütze H, Barth E, Martinetz T. An adaptive hierarchical sensing scheme for sparse signals Proceedings of Spie - the International Society For Optical Engineering. 9014. DOI: 10.1117/12.2043082 |
1 |
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| 2014 |
Burciu I, Ion-Margineanu A, Martinetz T, Barth E. Visual manifold sensing Proceedings of Spie - the International Society For Optical Engineering. 9014. DOI: 10.1117/12.2043012 |
1 |
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| 2014 |
Hocke J, Martinetz T. Maximum distance minimization for feature weighting Pattern Recognition Letters. 52: 48-52. DOI: 10.1016/j.patrec.2014.10.003 |
1 |
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| 2014 |
Hocke J, Martinetz T. Global metric learning by gradient descent Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 8681: 129-135. DOI: 10.1007/978-3-319-11179-7_17 |
1 |
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| 2014 |
Coleca F, Zîrnovean S, Käster T, Martinetz T, Barth E. Key-point detection with multi-layer center-surround inhibition Visapp 2014 - Proceedings of the 9th International Conference On Computer Vision Theory and Applications. 1: 386-393. |
1 |
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| 2013 |
Ngo HV, Martinetz T, Born J, Mölle M. Auditory closed-loop stimulation of the sleep slow oscillation enhances memory. Neuron. 78: 545-53. PMID 23583623 DOI: 10.1016/j.neuron.2013.03.006 |
1 |
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| 2013 |
Klement S, Anders S, Martinetz T. The support feature machine: classification with the least number of features and application to neuroimaging data. Neural Computation. 25: 1548-84. PMID 23517095 DOI: 10.1162/NECO_a_00447 |
1 |
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| 2013 |
Kandaswamy KK, Pugalenthi G, Kalies KU, Hartmann E, Martinetz T. EcmPred: prediction of extracellular matrix proteins based on random forest with maximum relevance minimum redundancy feature selection. Journal of Theoretical Biology. 317: 377-83. PMID 23123454 DOI: 10.1016/j.jtbi.2012.10.015 |
1 |
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| 2013 |
Coleca F, Klement S, Martinetz T, Barth E. Real-time skeleton tracking for embedded systems Proceedings of Spie - the International Society For Optical Engineering. 8667. DOI: 10.1117/12.2003004 |
1 |
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| 2013 |
Wellner M, Kastera T, Martinetz T, Barth E. Optimizing depth-of-field based on a range map and a wavelet transform Proceedings of Spie - the International Society For Optical Engineering. 8667. DOI: 10.1117/12.2002330 |
1 |
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| 2013 |
Coleca F, Martinetz T, Barth E. Gesture interfaces with depth sensors Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 8200: 207-227. DOI: 10.1007/978-3-642-44964-2_10 |
1 |
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| 2013 |
Hocke J, Martinetz T. Feature weighting by maximum distance minimization Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 8131: 420-425. DOI: 10.1007/978-3-642-40728-4_53 |
1 |
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| 2013 |
State A, Coleca F, Barth E, Martinetz T. Hand tracking with an extended self-organizing map Advances in Intelligent Systems and Computing. 198: 115-124. DOI: 10.1007/978-3-642-35230-0_12 |
1 |
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| 2013 |
Coman H, Barth E, Martinetz T. Sparse coding neural gas applied to image recognition Advances in Intelligent Systems and Computing. 198: 105-114. DOI: 10.1007/978-3-642-35230-0_11 |
1 |
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| 2012 |
Weigenand A, Martinetz T, Claussen JC. The phase response of the cortical slow oscillation. Cognitive Neurodynamics. 6: 367-75. PMID 24995052 DOI: 10.1007/s11571-012-9207-z |
1 |
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| 2012 |
Voigt J, Krause C, Rohwäder E, Saschenbrecker S, Hahn M, Danckwardt M, Feirer C, Ens K, Fechner K, Barth E, Martinetz T, Stöcker W. Automated indirect immunofluorescence evaluation of antinuclear autoantibodies on HEp-2 cells. Clinical & Developmental Immunology. 2012: 651058. PMID 23251220 DOI: 10.1155/2012/651058 |
1 |
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| 2012 |
Vig E, Dorr M, Martinetz T, Barth E. Intrinsic dimensionality predicts the saliency of natural dynamic scenes. Ieee Transactions On Pattern Analysis and Machine Intelligence. 34: 1080-91. PMID 22516647 DOI: 10.1109/TPAMI.2011.198 |
1 |
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| 2012 |
Binder T, Martinetz T. On the boundedness of an iteration involving points on the hypersphere International Journal of Computational Geometry and Applications. 22: 499-515. DOI: 10.1142/S0218195912500136 |
1 |
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| 2012 |
Hocke J, Barth E, Martinetz T. Application of non-linear transform coding to image processing Proceedings of Spie - the International Society For Optical Engineering. 8291. DOI: 10.1117/12.908732 |
1 |
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| 2012 |
Binder T, Kriener F, Wichner C, Wille M, Wellner M, Kaester T, Martinetz T, Barth E. How to make a small phone camera shoot like a big DSLR: Creating and fusing multi-modal exposure series Proceedings of Spie - the International Society For Optical Engineering. 8291. DOI: 10.1117/12.905560 |
1 |
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| 2012 |
Schütze H, Martinetz T, Anders S, Madany Mamlouk A. A multivariate approach to estimate complexity of FMRI time series Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 7553: 540-547. DOI: 10.1007/978-3-642-33266-1_67 |
1 |
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| 2011 |
Kandaswamy KK, Pugalenthi G, Hazrati MK, Kalies KU, Martinetz T. BLProt: prediction of bioluminescent proteins based on support vector machine and relieff feature selection. Bmc Bioinformatics. 12: 345. PMID 21849049 DOI: 10.1186/1471-2105-12-345 |
1 |
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| 2011 |
Zhang J, Mamlouk AM, Martinetz T, Chang S, Wang J, Hilgenfeld R. PhyloMap: an algorithm for visualizing relationships of large sequence data sets and its application to the influenza A virus genome. Bmc Bioinformatics. 12: 248. PMID 21689434 DOI: 10.1186/1471-2105-12-248 |
1 |
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| 2011 |
Kandaswamy KK, Chou KC, Martinetz T, Möller S, Suganthan PN, Sridharan S, Pugalenthi G. AFP-Pred: A random forest approach for predicting antifreeze proteins from sequence-derived properties. Journal of Theoretical Biology. 270: 56-62. PMID 21056045 DOI: 10.1016/j.jtbi.2010.10.037 |
1 |
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| 2011 |
Labusch K, Barth E, Martinetz T. Robust and fast learning of sparse codes with stochastic gradient descent Ieee Journal On Selected Topics in Signal Processing. 5: 1048-1060. DOI: 10.1109/JSTSP.2011.2149496 |
1 |
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| 2011 |
Lee JA, Schleif FM, Martinetz T. Advances in artificial neural networks, machine learning, and computational intelligence Neurocomputing. 74: 1299-1300. DOI: 10.1016/j.neucom.2011.02.003 |
1 |
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| 2011 |
Labusch K, Barth E, Martinetz T. Soft-competitive learning of sparse codes and its application to image reconstruction Neurocomputing. 74: 1418-1428. DOI: 10.1016/j.neucom.2011.02.002 |
1 |
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| 2011 |
Vig E, Dorr M, Martinetz T, Barth E. Eye Movements Show Optimal Average Anticipation with Natural Dynamic Scenes Cognitive Computation. 3: 79-88. DOI: 10.1007/s12559-010-9061-4 |
1 |
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| 2011 |
Klement S, Martinetz T. On the problem of finding the least number of features by L1-norm minimisation Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 6791: 315-322. DOI: 10.1007/978-3-642-21735-7_39 |
1 |
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| 2010 |
Pugalenthi G, Kandaswamy KK, Suganthan PN, Sowdhamini R, Martinetz T, Kolatkar PR. SMpred: a support vector machine approach to identify structural motifs in protein structure without using evolutionary information. Journal of Biomolecular Structure & Dynamics. 28: 405-14. PMID 20919755 DOI: 10.1080/07391102.2010.10507369 |
1 |
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| 2010 |
Dorr M, Martinetz T, Gegenfurtner KR, Barth E. Variability of eye movements when viewing dynamic natural scenes. Journal of Vision. 10: 28. PMID 20884493 DOI: 10.1167/10.10.28 |
1 |
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| 2010 |
Kandaswamy KK, Pugalenthi G, Möller S, Hartmann E, Kalies KU, Suganthan PN, Martinetz T. Prediction of apoptosis protein locations with genetic algorithms and support vector machines through a new mode of pseudo amino acid composition. Protein and Peptide Letters. 17: 1473-9. PMID 20666727 |
1 |
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| 2010 |
Kandaswamy KK, Pugalenthi G, Hartmann E, Kalies KU, Möller S, Suganthan PN, Martinetz T. SPRED: A machine learning approach for the identification of classical and non-classical secretory proteins in mammalian genomes. Biochemical and Biophysical Research Communications. 391: 1306-11. PMID 19995554 DOI: 10.1016/j.bbrc.2009.12.019 |
1 |
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| 2010 |
Timm F, Martinetz T. Statistical fourier descriptors for defect image classification Proceedings - International Conference On Pattern Recognition. 4190-4193. DOI: 10.1109/ICPR.2010.1018 |
1 |
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| 2010 |
Klement S, Martinetz T. A new approach to classification with the least number of features Proceedings - 9th International Conference On Machine Learning and Applications, Icmla 2010. 141-146. DOI: 10.1109/ICMLA.2010.28 |
1 |
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| 2010 |
Danielmeyer HG, Martinetz T. The biologic stability of the industrial evolution European Review. 18: 263-268. DOI: 10.1017/S106279870999041X |
1 |
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| 2010 |
Böhme M, Haker M, Martinetz T, Barth E. Shading constraint improves accuracy of time-of-flight measurements Computer Vision and Image Understanding. 114: 1329-1335. DOI: 10.1016/j.cviu.2010.08.001 |
1 |
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| 2010 |
Labusch K, Barth E, Martinetz T. Bag of pursuits and neural gas for improved sparse coding Proceedings of Compstat 2010 - 19th International Conference On Computational Statistics, Keynote, Invited and Contributed Papers. 327-336. DOI: 10.1007/978-3-7908-2604-3-30 |
1 |
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| 2010 |
Vig E, Dorr M, Martinetz T, Barth E. A learned saliency predictor for dynamic natural scenes Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 6354: 52-61. DOI: 10.1007/978-3-642-15825-4_6 |
1 |
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| 2010 |
Klement S, Martinetz T. The support feature machine for classifying with the least number of features Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 6353: 88-93. DOI: 10.1007/978-3-642-15822-3_11 |
1 |
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| 2010 |
Timm F, Martinetz T, Barth E. Optical inspection of welding seams Communications in Computer and Information Science. 68: 269-282. DOI: 10.1007/978-3-642-11840-1_20 |
1 |
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| 2010 |
Labusch K, Martinetz T. Learning sparse codes for image reconstruction Proceedings of the 18th European Symposium On Artificial Neural Networks - Computational Intelligence and Machine Learning, Esann 2010. 241-246. |
1 |
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| 2009 |
Martinetz T, Labusch K, Schneegass D. SoftDoubleMaxMinOver: perceptron-like training of support vector machines. Ieee Transactions On Neural Networks / a Publication of the Ieee Neural Networks Council. 20: 1061-72. PMID 19497817 DOI: 10.1109/TNN.2009.2016717 |
1 |
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| 2009 |
Repsilber D, Martinetz T, Björklund M. Adaptive dynamics of regulatory networks: size matters. Eurasip Journal On Bioinformatics & Systems Biology. 618502. PMID 19333363 DOI: 10.1155/2009/618502 |
1 |
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| 2009 |
Böhme M, Haker M, Martinetz T, Barth E. Head tracking with combined face and nose detection 2009 International Symposium On Signals, Circuits and Systems, Isscs 2009. DOI: 10.1109/ISSCS.2009.5206211 |
1 |
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| 2009 |
Labusch K, Barth E, Martinetz T. Sparse Coding Neural Gas: Learning of overcomplete data representations Neurocomputing. 72: 1547-1555. DOI: 10.1016/j.neucom.2008.11.027 |
1 |
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| 2009 |
Haker M, Böhme M, Martinetz T, Barth E. Deictic gestures with a time-of-flight camera Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 5934: 110-121. DOI: 10.1007/978-3-642-12553-9_10 |
1 |
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| 2009 |
Haker M, Martinetz T, Barth E. Multimodal sparse features for object detection Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 5769: 923-932. DOI: 10.1007/978-3-642-04277-5_93 |
1 |
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| 2009 |
Böhme M, Haker M, Riemer K, Martinetz T, Barth E. Face detection using a time-of-flight camera Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 5742: 167-176. DOI: 10.1007/978-3-642-03778-8_13 |
1 |
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| 2009 |
Haker M, Böhme M, Martinetz T, Barth E. Self-organizing maps for pose estimation with a time-of-flight camera Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 5742: 142-153. DOI: 10.1007/978-3-642-03778-8_11 |
1 |
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| 2009 |
Labusch K, Barth E, Martinetz T. Approaching the time dependent cocktail party problem with online sparse coding neural gas Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 5629: 145-153. DOI: 10.1007/978-3-642-02397-2_17 |
1 |
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| 2009 |
Labusch K, Barth E, Martinetz T. Demixing jazz-music: Sparse Coding Neural Gas for the separation of noisy overcomplete sources Neural Network World. 19: 581-596. |
1 |
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| 2009 |
Timm F, Klement S, Martinetz T, Barth E. Welding inspection using novel specularity features and a one-class SVM Visapp 2009 - Proceedings of the 4th International Conference On Computer Vision Theory and Applications. 1: 146-153. |
1 |
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| 2008 |
Labusch K, Barth E, Martinetz T. Simple method for high-performance digit recognition based on sparse coding. Ieee Transactions On Neural Networks / a Publication of the Ieee Neural Networks Council. 19: 1985-9. PMID 19000969 DOI: 10.1109/TNN.2008.2005830 |
1 |
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| 2008 |
Böhme M, Haker M, Martinetz T, Barth E. A facial feature tracker for human-computer interaction based on 3D Time-Of-Flight cameras International Journal of Intelligent Systems Technologies and Applications. 5: 264-273. DOI: 10.1504/IJISTA.2008.021289 |
1 |
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| 2008 |
Böhme M, Dorr M, Graw M, Martinetz T, Barth E. A software framework for simulating eye trackers Eye Tracking Research and Applications Symposium (Etra). 251-258. DOI: 10.1145/1344471.1344529 |
1 |
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| 2008 |
Schneegass D, Udluft S, Martinetz T. Uncertainty propagation for quality assurance in reinforcement learning Proceedings of the International Joint Conference On Neural Networks. 2588-2595. DOI: 10.1109/IJCNN.2008.4634160 |
1 |
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| 2008 |
Haker M, Böhme M, Martinetz T, Barth E. Scale-invariant range features for time-of-flight camera applications 2008 Ieee Computer Society Conference On Computer Vision and Pattern Recognition Workshops, Cvpr Workshops. DOI: 10.1109/CVPRW.2008.4563169 |
1 |
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| 2008 |
Labusch K, Barth E, Martinetz T. Sparse coding neural gas for the separation of noisy overcomplete sources Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 5163: 788-797. DOI: 10.1007/978-3-540-87536-9_81 |
1 |
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| 2008 |
Klement S, Madany Mamlouk A, Martinetz T. Reliability of cross-validation for SVMs in high-dimensional, low sample size scenarios Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 5163: 41-50. DOI: 10.1007/978-3-540-87536-9_5 |
1 |
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| 2008 |
Labusch K, Timm F, Martinetz T. Simple incremental one-class support vector classification Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 5096: 21-30. DOI: 10.1007/978-3-540-69321-5_3 |
1 |
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| 2008 |
Timm F, Klement S, Martinetz T. Fast model selection for MaxMinOver-based training of support vector machines Proceedings - International Conference On Pattern Recognition. |
1 |
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| 2008 |
Labusch K, Barth E, Martinetz T. Learning data representations with sparse coding neural gas Esann 2008 Proceedings, 16th European Symposium On Artificial Neural Networks - Advances in Computational Intelligence and Learning. 233-238. |
1 |
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| 2007 |
Labusch K, Siewert U, Martinetz T, Barth E. Learning optimal features for visual pattern recognition Proceedings of Spie - the International Society For Optical Engineering. 6492. DOI: 10.1117/12.713371 |
1 |
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| 2007 |
Haker M, Böhme M, Martinetz T, Barth E. Geometric invariants for facial feature tracking with 3D TOF cameras Isscs 2007 - International Symposium On Signals, Circuits and Systems, Proceedings. 1: 109-112. DOI: 10.1109/ISSCS.2007.4292663 |
1 |
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| 2007 |
Schneegaß D, Udluft S, Martinetz T. Improving optimality of neural rewards regression for data-efficient batch near-optimal policy identification Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 4668: 109-118. |
1 |
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| 2007 |
Schneegaß D, Schaefer AM, Martinetz T. The intrinsic recurrent support vector machine Esann 2007 Proceedings - 15th European Symposium On Artificial Neural Networks. 325-330. |
1 |
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| 2007 |
Schneegaß D, Udluft S, Martinetz T. Explicit kernel rewards regression for data-efficient near-optimal policy identification Esann 2007 Proceedings - 15th European Symposium On Artificial Neural Networks. 337-342. |
1 |
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| 2007 |
Schneegaß D, Udluft S, Martinetz T. Neural rewards regression for near-optimal policy identification in markovian and partial observable environments Esann 2007 Proceedings - 15th European Symposium On Artificial Neural Networks. 301-306. |
1 |
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| 2006 |
Barth E, Dorr M, Böhme M, Gegenfurtner K, Martinetz T. Guiding the mind's eye: Improving communication and vision by external control of the scanpath Proceedings of Spie - the International Society For Optical Engineering. 6057. DOI: 10.1117/12.674147 |
1 |
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| 2006 |
Martinetz T, Mamlouk AM, Mota C. Fast and easy computation of approximate smallest enclosing balls Brazilian Symposium of Computer Graphic and Image Processing. 163-168. DOI: 10.1109/SIBGRAPI.2006.20 |
1 |
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| 2006 |
Böhme M, Dorr M, Krause C, Martinetz T, Barth E. Eye movement predictions on natural videos Neurocomputing. 69: 1996-2004. DOI: 10.1016/j.neucom.2005.11.019 |
1 |
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| 2006 |
Dorr M, Böhme M, Martinetz T, Barth E. Gaze-contingent spatio-temporal filtering in a head-mounted display Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 4021: 205-207. DOI: 10.1007/11768029_24 |
1 |
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| 2006 |
Barth E, Dorr M, Böhme M, Gegenfurtner K, Martinetz T. Guiding eye movements for better communication and augmented vision Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 4021: 1-8. DOI: 10.1007/11768029_1 |
1 |
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| 2006 |
Schneegaß D, Udluft S, Martinetz T. Kernel rewards regression: An information efficient batch policy iteration approach Proceedings of the Iasted International Conference On Artificial Intelligence and Applications, Aia 2006. 428-433. |
1 |
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| 2006 |
Schneegaß D, Labusch K, Martinetz T. MaxMinOver regression: A simple incremental approach for support vector function approximation Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 4131: 150-158. |
1 |
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| 2006 |
Meyer A, Bõhme M, Martinetz T, Barth E. A single-camera remote eye tracker Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 4021: 208-211. |
1 |
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| 2005 |
Dorr M, Martinetz T, Böhme M, Barth E. Visibility of temporal blur on a gaze-contingent display Proceedings - Apgv 2005: 2nd Symposium On Applied Perception in Graphics and Visualization. 33-36. DOI: 10.1145/1080402.1080407 |
1 |
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| 2005 |
Mamlouk AM, Sharp H, Menne KML, Hofmann UG, Martinetz T. Unsupervised spike sorting with ICA and its evaluation using GENESIS simulations Neurocomputing. 65: 275-282. DOI: 10.1016/j.neucom.2004.10.019 |
1 |
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| 2005 |
Meyer-Bäse A, Jancke K, Wismüller A, Foo S, Martinetz T. Medical image compression using topology-preserving neural networks Engineering Applications of Artificial Intelligence. 18: 383-392. DOI: 10.1016/j.engappai.2004.10.004 |
1 |
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| 2005 |
Böhme M, Dorr M, Martinetz T, Barth E. Gaze-contingent temporal filtering of video Eye Tracking Research and Applications Symposium (Etra). 2005: 109-124. |
1 |
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| 2005 |
Martinetz T, Labusch K, Schneegaß D. SoftDoubleMinOver: A simple procedure for maximum margin classification Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 3697: 301-306. |
1 |
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| 2004 |
Kim JT, Gewehr JE, Martinetz T. Binding matrix: a novel approach for binding site recognition. Journal of Bioinformatics and Computational Biology. 2: 289-307. PMID 15297983 DOI: 10.1142/S0219720004000569 |
1 |
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| 2004 |
Martinetz T. MaxMinOver: A simple incremental learning procedure for support vector classification Ieee International Conference On Neural Networks - Conference Proceedings. 3: 2065-2070. DOI: 10.1109/IJCNN.2004.1380935 |
1 |
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| 2004 |
Mamlouk AM, Martinetz T. On the dimensions of the olfactory perception space Neurocomputing. 58: 1019-1025. DOI: 10.1016/j.neucom.2004.01.161 |
1 |
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| 2004 |
Martinetz T. MinOver Revisited for Incremental Support-Vector-Classification Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 3175: 187-194. |
1 |
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| 2003 |
Kim JT, Martinetz T, Polani D. Bioinformatic principles underlying the information content of transcription factor binding sites. Journal of Theoretical Biology. 220: 529-44. PMID 12623284 DOI: 10.1006/jtbi.2003.3153 |
1 |
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| 2003 |
Barth E, Drewes J, Martinetz T. Individual predictions of eye-movements with dynamic scenes Proceedings of Spie - the International Society For Optical Engineering. 5007: 252-259. DOI: 10.1117/12.477374 |
1 |
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| 2003 |
Barth E, Drewes J, Martinetz T. Dynamic predictions of tracked gaze Proceedings - 7th International Symposium On Signal Processing and Its Applications, Isspa 2003. 1: 245-248. DOI: 10.1109/ISSPA.2003.1224686 |
1 |
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| 2003 |
Mamlouk AM, Kim JT, Barth E, Brauckmann M, Martinetz T. One-class classification with subgaussians Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 2781: 346-353. |
1 |
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| 2003 |
Martinetz T, Gewehr JE, Kim JT. Statistical Learning for Detecting Protein-DNA-Binding Sites Proceedings of the International Joint Conference On Neural Networks. 4: 2940-2945. |
1 |
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| 2002 |
Haker M, Meyer A, Polani D, Martinetz T. A method for incorporation of new evidence to improve world state estimation Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 2377: 362-367. |
1 |
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| 2001 |
Polani D, Martinetz T. Team description for Lucky Lübeck - Evidence-based World state Estimation Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 2019: 481-484. |
1 |
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| 2001 |
Wilke CO, Ronnewinkel C, Martinetz T. Dynamic fitness landscapes in molecular evolution Physics Report. 349: 395-446. |
1 |
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| 2001 |
Polani D, Martinetz T, Kim J. An information-theoretic approach for the quantification of relevance Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 2159: 704-713. |
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| 1999 |
Wilke CO, Martinetz T. Adaptive walks on time-dependent fitness landscapes. Physical Review. E, Statistical Physics, Plasmas, Fluids, and Related Interdisciplinary Topics. 60: 2154-9. PMID 11970008 |
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| 1999 |
Wilke CO, Ronnewinkel C, Martinetz T. Molecular evolution in time-dependent environments Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 1674: 417-421. DOI: 10.1007/3-540-48304-7_57 |
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| 1998 |
Wilke C, Martinetz T. Hierarchical noise in large systems of independent agents Physical Review E - Statistical Physics, Plasmas, Fluids, and Related Interdisciplinary Topics. 58: 7101-7108. |
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| 1998 |
Wilke C, Altmeyer S, Martinetz T. Aftershocks in coherent-noise models Physica D: Nonlinear Phenomena. 120: 401-417. |
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| 1997 |
Villmann T, Der R, Herrmann M, Martinetz TM. Topology preservation in self-organizing feature maps: exact definition and measurement. Ieee Transactions On Neural Networks / a Publication of the Ieee Neural Networks Council. 8: 256-66. PMID 18255630 DOI: 10.1109/72.557663 |
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| 1997 |
Wilke C, Martinetz T. Simple model of evolution with variable system size Physical Review E - Statistical Physics, Plasmas, Fluids, and Related Interdisciplinary Topics. 56: 7128-7131. |
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| 1994 |
Martinetz T, Schulten K. Topology representing networks Neural Networks. 7: 507-522. DOI: 10.1016/0893-6080(94)90109-0 |
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| 1993 |
Martinetz TM, Berkovich SG, Schulten KJ. ;Neural-gas' network for vector quantization and its application to time-series prediction. Ieee Transactions On Neural Networks / a Publication of the Ieee Neural Networks Council. 4: 558-69. PMID 18267757 DOI: 10.1109/72.238311 |
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| 1993 |
Martinetz T, Schulten K. A neural network with hebbian-like adaptation rules learning visuomotor coordination of a PUMA robot Ieee International Conference On Neural Networks - Conference Proceedings. 1993: 820-822. DOI: 10.1109/ICNN.1993.298661 |
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| 1993 |
Martinetz T, Schulten K. A neural network for robot control: Cooperation between neural units as a requirement for learning Computers and Electrical Engineering. 19: 315-332. DOI: 10.1016/0045-7906(93)90053-T |
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| 1990 |
Martinetz TM, Ritter HJ, Schulten KJ. Three-dimensional neural net for learning visuomotor coordination of a robot arm. Ieee Transactions On Neural Networks / a Publication of the Ieee Neural Networks Council. 1: 131-6. PMID 18282830 DOI: 10.1109/72.80212 |
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| 1989 |
Ritter HJ, Martinetz TM, Schulten KJ. Topology-conserving maps for learning visuo-motor-coordination Neural Networks. 2: 159-168. DOI: 10.1016/0893-6080(89)90001-4 |
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