Thomas Martinetz

	2012
69		Eleonora Vig, Michael Dorr, Thomas Martinetz, Erhardt Barth: Intrinsic Dimensionality Predicts the Saliency of Natural Dynamic Scenes. IEEE Trans. Pattern Anal. Mach. Intell. 34(6): 1080-1091 (2012)
	2011
68		Sascha Klement, Thomas Martinetz: On the Problem of Finding the Least Number of Features by L1-Norm Minimisation. ICANN (1) 2011: 315-322
67		Jiajie Zhang, Amir Madany Mamlouk, Thomas Martinetz, Suhua Chang, Jing Wang, Rolf Hilgenfeld: PhyloMap: an algorithm for visualizing relationships of large sequence data sets and its application to the influenza A virus genome. BMC Bioinformatics 12: 248 (2011)
66		Krishna Kumar Kandaswamy, Ganesan Pugalenthi, Mehrnaz Khodam Hazrati, Kai-Uwe Kalies, Thomas Martinetz: BLProt: Prediction of bioluminescent proteins based on Support Vector Machine and ReliefF feature selection. BMC Bioinformatics 12: 345 (2011)
65		Eleonora Vig, Michael Dorr, Thomas Martinetz, Erhardt Barth: Eye Movements Show Optimal Average Anticipation with Natural Dynamic Scenes. Cognitive Computation 3(1): 79-88 (2011)
64		Kai Labusch, Erhardt Barth, Thomas Martinetz: Robust and Fast Learning of Sparse Codes With Stochastic Gradient Descent. J. Sel. Topics Signal Processing 5(5): 1048-1060 (2011)
63		John A. Lee, Frank-Michael Schleif, Thomas Martinetz: Advances in artificial neural networks, machine learning, and computational intelligence. Neurocomputing 74(9): 1299-1300 (2011)
62		Kai Labusch, Erhardt Barth, Thomas Martinetz: Soft-competitive learning of sparse codes and its application to image reconstruction. Neurocomputing 74(9): 1418-1428 (2011)
	2010
61		Kai Labusch, Thomas Martinetz: Learning sparse codes for image reconstruction. ESANN 2010
60		Sascha Klement, Thomas Martinetz: The Support Feature Machine for Classifying with the Least Number of Features. ICANN (2) 2010: 88-93
59		Eleonora Vig, Michael Dorr, Thomas Martinetz, Erhardt Barth: A Learned Saliency Predictor for Dynamic Natural Scenes. ICANN (3) 2010: 52-61
58		Sascha Klement, Thomas Martinetz: A New Approach to Classification with the Least Number of Features. ICMLA 2010: 141-146
57		Fabian Timm, Thomas Martinetz: Statistical Fourier Descriptors for Defect Image Classification. ICPR 2010: 4190-4193
56		Thomas Binder, Thomas Martinetz: On the boundedness of an iteration involving points on the hypersphere CoRR abs/1001.1624: (2010)
55		Martin Böhme, Martin Haker, Thomas Martinetz, Erhardt Barth: Shading constraint improves accuracy of time-of-flight measurements. Computer Vision and Image Understanding 114(12): 1329-1335 (2010)
	2009
54		Martin Haker, Martin Böhme, Thomas Martinetz, Erhardt Barth: Self-Organizing Maps for Pose Estimation with a Time-of-Flight Camera. Dyn3D 2009: 142-153
53		Martin Böhme, Martin Haker, Kolja Riemer, Thomas Martinetz, Erhardt Barth: Face Detection Using a Time-of-Flight Camera. Dyn3D 2009: 167-176
52		Martin Haker, Martin Böhme, Thomas Martinetz, Erhardt Barth: Deictic Gestures with a Time-of-Flight Camera. Gesture Workshop 2009: 110-121
51		Martin Haker, Thomas Martinetz, Erhardt Barth: Multimodal Sparse Features for Object Detection. ICANN (2) 2009: 923-932
50		Fabian Timm, Sascha Klement, Thomas Martinetz, Erhardt Barth: Welding Inspection using Novel Specularity Features and a One-class SVM. VISAPP (1) 2009: 146-153
49		Kai Labusch, Erhardt Barth, Thomas Martinetz: Approaching the Time Dependent Cocktail Party Problem with Online Sparse Coding Neural Gas. WSOM 2009: 145-153
48		Dirk Repsilber, Thomas Martinetz, Mats Björklund: Adaptive Dynamics of Regulatory Networks: Size Matters. EURASIP J. Bioinformatics and Systems Biology 2009: (2009)
47		Thomas Martinetz, Kai Labusch, Daniel Schneegaß: SoftDoubleMaxMinOver: Perceptron-Like Training of Support Vector Machines. IEEE Transactions on Neural Networks 20(7): 1061-1072 (2009)
46		Kai Labusch, Erhardt Barth, Thomas Martinetz: Sparse Coding Neural Gas: Learning of overcomplete data representations. Neurocomputing 72(7-9): 1547-1555 (2009)
	2008
45		Kai Labusch, Fabian Timm, Thomas Martinetz: Simple Incremental One-Class Support Vector Classification. DAGM-Symposium 2008: 21-30
44		Kai Labusch, Erhardt Barth, Thomas Martinetz: Learning Data Representations with Sparse Coding Neural Gas. ESANN 2008: 233-238
43		Martin Böhme, Michael Dorr, Mathis Graw, Thomas Martinetz, Erhardt Barth: A software framework for simulating eye trackers. ETRA 2008: 251-258
42		Sascha Klement, Amir Madany Mamlouk, Thomas Martinetz: Reliability of Cross-Validation for SVMs in High-Dimensional, Low Sample Size Scenarios. ICANN (1) 2008: 41-50
41		Kai Labusch, Erhardt Barth, Thomas Martinetz: Sparse Coding Neural Gas for the Separation of Noisy Overcomplete Sources. ICANN (1) 2008: 788-797
40		Fabian Timm, Sascha Klement, Thomas Martinetz: Fast model selection for MaxMinOver-based training of support vector machines. ICPR 2008: 1-4
39		Daniel Schneegaß, Steffen Udluft, Thomas Martinetz: Uncertainty propagation for quality assurance in Reinforcement Learning. IJCNN 2008: 2588-2595
38		Kai Labusch, Erhardt Barth, Thomas Martinetz: Simple Method for High-Performance Digit Recognition Based on Sparse Coding. IEEE Transactions on Neural Networks 19(11): 1985-1989 (2008)
37		Martin Böhme, Martin Haker, Thomas Martinetz, Erhardt Barth: A facial feature tracker for human-computer interaction based on 3D Time-Of-Flight cameras. IJISTA 5(3/4): 264-273 (2008)
	2007
36		Daniel Schneegaß, Steffen Udluft, Thomas Martinetz: Neural Rewards Regression for near-optimal policy identification in Markovian and partial observable environments. ESANN 2007: 301-306
35		Daniel Schneegaß, Anton Maximilian Schäfer, Thomas Martinetz: The Intrinsic Recurrent Support Vector Machine. ESANN 2007: 325-330
34		Daniel Schneegaß, Steffen Udluft, Thomas Martinetz: Explicit Kernel Rewards Regression for data-efficient near-optimal policy identification. ESANN 2007: 337-342
33		Daniel Schneegaß, Steffen Udluft, Thomas Martinetz: Improving Optimality of Neural Rewards Regression for Data-Efficient Batch Near-Optimal Policy Identification. ICANN (1) 2007: 109-118
	2006
32		Daniel Schneegaß, Steffen Udluft, Thomas Martinetz: Kernel Rewards Regression: An Information Efficient Batch Policy Iteration Approach. Artificial Intelligence and Applications 2006: 428-433
31		Daniel Schneegaß, Thomas Martinetz, Michael Clausohm: OnlineDoubleMaxMinOver: a simple approximate time and information efficient online Support Vector Classification method. ESANN 2006: 575-580
30		Martin Böhme, Michael Dorr, Thomas Martinetz, Erhardt Barth: Gaze-contingent temporal filtering of video. ETRA 2006: 109-115
29		Daniel Schneegaß, Kai Labusch, Thomas Martinetz: MaxMinOver Regression: A Simple Incremental Approach for Support Vector Function Approximation. ICANN (1) 2006: 150-158
28		Erhardt Barth, Michael Dorr, Martin Böhme, Karl R. Gegenfurtner, Thomas Martinetz: Guiding Eye Movements for Better Communication and Augmented Vision. PIT 2006: 1-8
27		Michael Dorr, Martin Böhme, Thomas Martinetz, Erhardt Barth: Gaze-Contingent Spatio-temporal Filtering in a Head-Mounted Display. PIT 2006: 205-207
26		André Meyer, Martin Böhme, Thomas Martinetz, Erhardt Barth: A Single-Camera Remote Eye Tracker. PIT 2006: 208-211
25		Thomas Martinetz, Amir Madany Mamlouk, Cicero Mota: Fast and Easy Computation of Approximate Smallest Enclosing Balls. SIBGRAPI 2006: 163-170
24		Martin Böhme, Michael Dorr, Christopher Krause, Thomas Martinetz, Erhardt Barth: Eye movement predictions on natural videos. Neurocomputing 69(16-18): 1996-2004 (2006)
	2005
23		Uwe Brinkschulte, Jürgen Becker, Dietmar Fey, Christian Hochberger, Thomas Martinetz, Christian Müller-Schloer, Hartmut Schmeck, Theo Ungerer, Rolf P. Würtz: 18th International Conference on Architecture of Computing Systems, Workshops, Innsbruck, Austria, March 2005 VDE Verlag 2005
22		Michael Dorr, Thomas Martinetz, Martin Böhme, Erhardt Barth: Visibility of temporal blur on a gaze-contingent display. APGV 2005: 33-36
21		Thomas Martinetz, Kai Labusch, Daniel Schneegaß: SoftDoubleMinOver: A Simple Procedure for Maximum Margin Classification. ICANN (2) 2005: 301-306
20		Anke Meyer-Bäse, Karsten Jancke, Axel Wismüller, Simon Foo, Thomas Martinetz: Medical image compression using topology-preserving neural networks. Eng. Appl. of AI 18(4): 383-392 (2005)
19		Amir Madany Mamlouk, Hannah Sharp, Kerstin M. L. Menne, Ulrich G. Hofmann, Thomas Martinetz: Unsupervised spike sorting with ICA and its evaluation using GENESIS simulations. Neurocomputing 65-66: 275-282 (2005)
	2004
18		Thomas Martinetz: MinOver Revisited for Incremental Support-Vector-Classification. DAGM-Symposium 2004: 187-194
17		Martin Böhme, Christopher Krause, Thomas Martinetz, Erhardt Barth: Saliency Extraction for Gaze-Contingent Displays. GI Jahrestagung (2) 2004: 646-650
16		Jan T. Kim, Jan E. Gewehr, Thomas Martinetz: Binding Matrix: a Novel Approach for Binding Site Recognition. J. Bioinformatics and Computational Biology 2(2): 289-308 (2004)
	2003
15		Amir Madany Mamlouk, Jan T. Kim, Erhardt Barth, Michael Brauckmann, Thomas Martinetz: One-Class Classification with Subgaussians. DAGM-Symposium 2003: 346-353
14		Anke Meyer-Bäse, Thomas D. Otto, Thomas Martinetz, Dorothee Auer, Axel Wismüller: Model-Free Functional MRI Analysis Using Topographic Independent Component Analysis. ESANN 2003: 509-514
	2001
13		Daniel Polani, Thomas Martinetz, Jan T. Kim: An Information-Theoretic Approach for the Quantification of Relevance. ECAL 2001: 704-713
12		Jan T. Kim, Thomas Martinetz, Daniel Polani: On the Effects of Transcription Factor Properties on the Information Content of Binding Sites. German Conference on Bioinformatics 2001: 192-194
11		Martin Haker, André Meyer, Daniel Polani, Thomas Martinetz: A Method for Incorporation of New Evidence to Improve World State Estimation. RoboCup 2001: 362-367
	2000
10		Daniel Polani, Thomas Martinetz: Team Description for Lucky Lübeck - Evidence-Based World State Estimation. RoboCup 2000: 481-484
	1999
9		Claus O. Wilke, Christopher Ronnewinkel, Thomas Martinetz: Molecular Evolution in Time-Dependent Environments. ECAL 1999: 417-421
8		Christopher Ronnewinkel, Claus O. Wilke, Thomas Martinetz: Genetic Algorithms in Time-Dependent Environments CoRR physics/9911006: (1999)
	1994
7		Thomas Villmann, Ralf Der, J. Michael Herrmann, Thomas Martinetz: Topology Preservation in Self-Organizing Feature Maps: General Definition and Efficient Measurement. Fuzzy Days 1994: 159-166
6		Thomas Martinetz, Klaus Schulten: Topology representing networks. Neural Networks 7(3): 507-522 (1994)
	1992
5		Helge Ritter, Thomas Martinetz, Klaus Schulten: Neural computation and self-organizing maps - an introduction. Addison-Wesley 1992: 1-306
4		Thomas Martinetz: Selbstorganisierende neuronale Netzwerkmodelle zur Bewegungssteuerung. Infix Verlag, St. Augustin, Germany 1992
	1991
3		Helge Ritter, Thomas Martinetz, Klaus Schulten: Neuronale Netze - eine Einführung in die Neuroinformatik selbstorganisierter Netzwerke (2. Aufl.). Addison-Wesley 1991: 1-325
2		Stan Berkovitch, Philippe Dalger, Ted Hesselroth, Thomas Martinetz, Benoît Noël, Jörg A. Walter, Klaus Schulten: Vector Quantization Algorithm for Time Series Prediction and Visuo-Motor Control of Robots. Wissensbasierte Systeme 1991: 443-447
	1989
1		Helge Ritter, Thomas Martinetz, Klaus Schulten: Topology-conserving maps for learning visuo-motor-coordination. Neural Networks 2(3): 159-168 (1989)

Coauthor Index

1	Dorothee Auer (Dorothee P. Auer)	[14]
2	Erhardt Barth	[15] [17] [22] [24] [26] [27] [28] [30] [37] [38] [41] [43] [44] [46] [49] [50] [51] [52] [53] [54] [55] [59] [62] [64] [65] [69]
3	Jürgen Becker	[23]
4	Stan Berkovitch	[2]
5	Thomas Binder	[56]
6	Mats Björklund	[48]
7	Martin Böhme	[17] [22] [24] [26] [27] [28] [30] [37] [43] [52] [53] [54] [55]
8	Michael Brauckmann	[15]
9	Uwe Brinkschulte	[23]
10	Suhua Chang	[67]
11	Michael Clausohm	[31]
12	Philippe Dalger	[2]
13	Ralf Der	[7]
14	Michael Dorr	[22] [24] [27] [28] [30] [43] [59] [65] [69]
15	Dietmar Fey	[23]
16	Simon Foo	[20]
17	Karl R. Gegenfurtner	[28]
18	Jan E. Gewehr	[16]
19	Mathis Graw	[43]
20	Martin Haker	[11] [37] [51] [52] [53] [54] [55]
21	Mehrnaz Khodam Hazrati	[66]
22	J. Michael Herrmann	[7]
23	Ted Hesselroth	[2]
24	Rolf Hilgenfeld	[67]
25	Christian Hochberger	[23]
26	Ulrich G. Hofmann	[19]
27	Karsten Jancke	[20]
28	Kai-Uwe Kalies	[66]
29	Krishna Kumar Kandaswamy	[66]
30	Jan T. Kim	[12] [13] [15] [16]
31	Sascha Klement	[40] [42] [50] [58] [60] [68]
32	Christopher Krause	[17] [24]
33	Kai Labusch	[21] [29] [38] [41] [44] [45] [46] [47] [49] [61] [62] [64]
34	John A. Lee	[63]
35	Amir Madany Mamlouk	[15] [19] [25] [42] [67]
36	Kerstin M. L. Menne	[19]
37	André Meyer	[11] [26]
38	Anke Meyer-Bäse	[14] [20]
39	Cicero Mota	[25]
40	Christian Müller-Schloer	[23]
41	Benoît Noël	[2]
42	Thomas D. Otto	[14]
43	Daniel Polani	[10] [11] [12] [13]
44	Ganesan Pugalenthi	[66]
45	Dirk Repsilber	[48]
46	Kolja Riemer	[53]
47	Helge J. Ritter (Helge Ritter)	[1] [3] [5]
48	Christopher Ronnewinkel	[8] [9]
49	Anton Maximilian Schäfer	[35]
50	Frank-Michael Schleif	[63]
51	Hartmut Schmeck	[23]
52	Daniel Schneegaß	[21] [29] [31] [32] [33] [34] [35] [36] [39] [47]
53	Klaus Schulten	[1] [2] [3] [5] [6]
54	Hannah Sharp	[19]
55	Fabian Timm	[40] [45] [50] [57]
56	Steffen Udluft	[32] [33] [34] [36] [39]
57	Theo Ungerer	[23]
58	Eleonora Vig	[59] [65] [69]
59	Thomas Villmann	[7]
60	Jörg A. Walter	[2]
61	Jing Wang	[67]
62	Claus O. Wilke	[8] [9]
63	Axel Wismüller	[14] [20]
64	Rolf P. Würtz	[23]
65	Jiajie Zhang	[67]

Colors in the list of coauthors

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