Institute of Cognitive Science

Research Group Computer Vision


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Publications

Journal Articles

[1] B. Höferlin, M. Höferlin, G. Heidemann & D. Weiskopf.
Scalable video visual analytics.
Information Visualization, 14(1) : 10-26, 2015.
| DOI | BibTeX
[2] P. Tanisaro, J. Schöning, K. Kurzhals, G. Heidemann & D. Weiskopf.
Visual analytics for video applications.
it-Information Technology, 57 : 30-36, 2015. De Gruyter.
| DOI | BibTeX
[3] M. Höferlin, B. Höferlin, G. Heidemann & D. Weiskopf.
Interactive Schematic Summaries for Faceted Exploration of Surveillance Video.
IEEE Transactions on Multimedia, 15(4) : 908-920, 2013.
| PDF | DOI | BibTeX
[4] M. Höferlin, K. Kurzhals, B. Höferlin, G. Heidemann & D. Weiskopf.
Evaluation of Fast-Forward Video Visualization.
IEEE Transactions on Visualization and Computer Graphics (TVCG), 18(12) : 2095-2103, 2012.
| PDF | DOI | BibTeX
[5] M. Höferlin, B. Höferlin, D. Weiskopf & G. Heidemann.
Uncertainty-Aware Video Visual Analytics of Tracked Moving Objects.
Journal of Spatial Information Science (JOSIS), 2 : 87-117, 2011.
| PDF | DOI | BibTeX
[6] B. Höferlin, M. Höferlin, D. Weiskopf & G. Heidemann.
Information-Based Adaptive Fast-Forward for Visual Surveillance.
Multimedia Tools and Applications, 55(1) : 127-150, 2011. Springer Netherlands.
| PDF | DOI | BibTeX
[7] M. Gabb, O. Lohlein, M. Oberlander & G. Heidemann.
Efficient monocular vehicle orientation estimation using a tree-based classifier.
IEEE Intelligent Vehicles Symposium (IV), pages: 308-313, 2011. IEEE.
| DOI | BibTeX
[8] S. Klenk, J. Dippon, P. Fritz & G. Heidemann.
Interactive Survival Analysis with the OCDM system: From Development to Application.
Information Systems Frontiers, 11 : 391-403, 2009. Springer.
| PDF | DOI | BibTeX
[9] C. Bauckhage, S. Wachsmuth, M. Hanheide, S. Wrede, G. Sagerer, G. Heidemann & H. Ritter.
The Visual Active Memory Perspective on Integrated Recognition Systems.
Image and Vision Computing, 26 : 5-14, 2008.
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[10] G. Heidemann.
Region Saliency as a Measure for Colour Segmentation Stability.
Image and Vision Computing, 26 : 211-227, 2008.
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[11] G. Heidemann, H. Bekel, I. Bax & H. Ritter.
Interactive Online Learning.
Pattern Recognition and Image Analysis, 17(1) : 146-152, 2007.
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[12] G. Heidemann.
The Principal Components of Natural Images Revisited.
IEEE Trans. on Pattern Analysis and Machine Intelligence, 28(5) : 822-826, 2006.
| PDF | DOI | BibTeX
[13] I. Bax, G. Heidemann & H. Ritter.
A Hierarchical Feedforward Network for Object Detection Tasks.
J. Opt. Eng., 45(6) : (067203-19-(067203-10), 2006.
| PDF | DOI | BibTeX
[14] H. Bekel, G. Heidemann & H. Ritter.
Interactive Image Data Labeling Using Self-Organizing Maps in an Augmented Reality Scenario.
Neural Networks, 18(5/6) : 566-574, 2005.
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[15] G. Heidemann, H. Bekel, I. Bax & H. Ritter.
Interactive Online Learning.
Pattern Recognition and Image Analysis, 15(1) : 55-58, 2005.
| PDF | BibTeX
[16] G. Heidemann.
The Long-Range Saliency of Edge- and Corner-Based Salient Points.
IEEE Trans. on Image Processing, 14(11) : 1701-1706, 2005.
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[17] G. Heidemann.
Unsupervised Image Categorization.
Image and Vision Computing, 23 : 861-876, 2005.
| PDF | DOI | BibTeX
[18] G. Heidemann, R. Rae, H. Bekel, I. Bax & H. Ritter.
Integrating Context-Free and Context-Dependent Attentional Mechanisms for Gestural Object Reference.
Machine Vision and Applications, 16(1) : 64-73, 2004.
| PDF | DOI | BibTeX
[19] G. Heidemann.
Combining spatial and Colour Information for Content Based Image Retrieval.
Computer Vision and Image Understanding, Special Issue on Colour for Image Indexing and Retrieval, 94(1-3) : 234-270, 2004.
| PDF | DOI | BibTeX
[20] G. Heidemann.
Focus-of-Attention from Local Color Symmetries.
IEEE Trans. on Pattern Analysis and Machine Intelligence, 26(7) : 817-830, 2004.
| PDF | DOI | BibTeX
[21] G. Heidemann & H. Ritter.
Learning to Recognise Objects and Situations to Control a Robot End-Effector.
KI Künstliche Intelligenz, Special Issue on Vision, Learning, Robotics, 2 : 24-29, 2003.
| PDF | BibTeX
[22] G. Heidemann & H. Ritter.
Efficient Vector Quantization Using the WTA-rule with Activity Equalization.
Neural Processing Letters, 13(1) : 17-30, 2001.
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[23] C. Bauckhage, G.A. Fink, G. Heidemann, N. Jungclaus, F. Kummert, S. Posch, H. Ritter, G. Sagerer & D. Schlüter.
Towards an Image Understanding Architecture for a Situated Artificial Communicator.
Pattern Recognition and Image Analysis, 9(4) : 542-548, 1999.
| PDF | BibTeX
[24] C. Bahlmann, G. Heidemann & H. Ritter.
Artificial Neural Networks for Automated Quality Control of Textile Seams.
Pattern Recognition, 32 : 1049-1060, 1999.
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[25] G. Heidemann, N. Jungclaus, F. Kummert, G. Sagerer & H. Ritter.
Ein hybrides Bildanalyse-System für einen künstlichen Kommunikator.
Kognitionswissenschaft (Sonderheft), 8(3) : 101-107, 1999.
| PDF | BibTeX
[26] E. Braun, G. Heidemann, H. Ritter & G. Sagerer.
A Multi-Directional Multiple-Path Recognition Scheme for Complex Objects applied to the Domain of a Wooden Toy Kit.
Pattern Recognition Letters, 20(11-13) : 1085-1091, 1999.
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[27] G. Heidemann, M. Bode & H.G. Purwins.
Fronts between Hopf- and Turing-Type Domains in a Two-Component Reaction-diffusion System.
Physics Letters A, 177 : 225-230, 1993.
| PDF | DOI | BibTeX

Conference Contributions

[1] J. Schöning, T. Behrens, P. Faion, P. Kheiri, G. Heidemann & U. Krumnack.
Structure from Motion by Artificial Neural Networks.
In Scandinavian Conference on Image Analysis (SCIA) 2017. Springer Nature [InPress].
| URL | BibTeX
[2] J. Schöning, P. Faion, G. Heidemann & U. Krumnack.
Providing Video Annotations in Multimedia Containers for Visualization and Research.
In IEEE Winter Conference on Applications of Computer Vision (WACV) 2017. IEEE [InPress].
| URL | BibTeX
[3] J. Schöning, A.L. Gert, A. Açik, T.C. Kietzmann, G. Heidemann & P. König.
Exploratory Multimodal Data Analysis with Standard Multimedia Player --- Multimedia Containers: a Feasible Solution to make Multimodal Research Data Accessible to the Broad Audience.
In Proceedings of the 12th Joint Conference on Computer Vision, Imagingand Computer Graphics Theory and Applications (VISAPP), pages: 272-279, ISBN: 978-989-758-225-7, 2017. SCITEPRESS.
| PDF | DOI | URL | BibTeX
[4] J. Schöning, P. Faion & G. Heidemann.
Pixel-wise Ground Truth Annotation in Videos - An Semi-automaticApproach for Pixel-wise and Semantic Object Annotation.
In Proceedings of the 5th International Conference on Pattern Recognition Applications and Methods (ICPRAM-2016), pages: 690-697, ISBN: 978-989-758-173-1, 2016. SCITEPRESS.
| PDF | DOI | BibTeX
[5] J. Schöning, P. Faion, G. Heidemann & U. Krumnack.
Eye Tracking Data in Multimedia Containers for Instantaneous Visualizations.
In IEEE VIS Workshop on Eye Tracking and Visualization (ETVIS), pages: 74-78, 2016. IEEE.
| PDF | DOI | URL | BibTeX
[6] J. Schöning, P. Faion & G. Heidemann.
Interactive Feature Growing for Accurate Object Detection in Megapixel Images.
Computer Vision – ECCV 2016 Workshops, 9913 : 546-556, ISBN: 978-3-319-46604-0, 2016. Springer Nature.
| PDF | DOI | URL | BibTeX
[7] J. Schöning & G. Heidemann.
Taxonomy of 3D Sensors - A Survey of State-of-the-Art Consumer 3D-Reconstruction Sensors and Their Field of Applications.
In Proceedings of the 11th Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISAPP 2016), 3 : 194-199, ISBN: 978-989-758-175-5, 2016. SCITEPRESS.
| PDF | DOI | BibTeX
[8] J. Schöning & G. Heidemann.
Image Based Spare Parts Reconstruction for Repairing Vital Infrastructure after Disasters.
In Global Humanitarian Technology Conference (GHTC), pages: 225-232, 2016. IEEE.
| PDF | DOI | BibTeX
[9] J. Schöning & G. Heidemann.
Bio-Inspired Architecture for Deriving 3D Models from Video Sequences.
Computer Vision -- ACCV 2016 Workshop, pages: 62-76, ISBN: 978-3-319-54427-4, 2016. Springer Nature.
| PDF | DOI | URL | BibTeX
[10] P. Tanisaro & G. Heidemann.
Time Series Classification Using Time Warping Invariant Echo State Networks.
In Confonference on Machine Learning and Application (ICMLA) 2016. IEEE [InPress].
| BibTeX
[11] J. Moehrmann & G. Heidemann.
FOREST - A Flexible Object Recognition System.
In Proceedings of the International Conference on Pattern Recognition Applications and Methods (ICPRAM-2015), 2 : 119-127, ISBN: 978-989-758-077-2, 2015. SCITEPRESS.
| DOI | BibTeX
[12] J. Schöning & G. Heidemann.
Interactive 3D Modeling - A Survey-based Perspective on Interactive 3D Reconstruction.
In Proceedings of the 4th International Conference on Pattern Recognition Applications and Methods (ICPRAM-2015), 2 : 289-294, ISBN: 978-989-758-077-2, 2015. SCITEPRESS.
| PDF | DOI | BibTeX
[13] J. Schöning, P. Faion & G. Heidemann.
Semi-automatic Ground Truth Annotation in Videos: An InteractiveTool for Polygon-based Object Annotation and Segmentation.
In Proceedings of the 8th International Conference on Knowledge Capture, pages: 17:1-17:4, ISBN: 978-1-4503-3849-3, 2015. ACM, New York.
| DOI | BibTeX
[14] J. Moehrmann & G. Heidemann.
Semi-Interactive Image Annotation with Visual Feedback.
In ECCV Workshop on Human-Machine Communication for Visual Recognition and Search 2014.
| PDF | BibTeX
[15] J. Moehrmann & G. Heidemann.
Efficient development of user-defined image recognition systems.
In Computer Vision-ACCV 2012 Workshops, 7728 : 242-253, ISBN: 978-3-642-37409-8, 2013.
| DOI | URL | BibTeX
[16] J. Moehrmann & G. Heidemann.
Semi-automatic Image Annotation.
In Computer Analysis of Images and Patterns, 8048 : 266-273, ISBN: 978-3-642-40245-6, 2013.
| DOI | BibTeX
[17] J. Moehrmann & G. Heidemann.
Efficient Annotation of Image Data Sets for Computer Vision Applications.
In Proceedings of the 1st International Workshop on Visual Interfaces for Ground Truth Collection in Computer Vision Applications, pages: 2:1-2:6, 2012. ACM.
| DOI | BibTeX
[18] R. Borgo, M. Chen, B. Daubney, E. Grundy, G. Heidemann, B. Höferlin, M. Höferlin, H. Leitte, D. Weiskopf & X. Xie.
State of the Art Report on Video-Based Graphics and Video Visualization.
In Computer Graphics Forum, 31(8) : 2450-2477, 2012.
| DOI | BibTeX
[19] B. Höferlin, M. Höferlin, B. Goloubets, G. Heidemann & D. Weiskopf.
Auditory Support for Situation Awareness in Video Surveillance.
In In Proceedings of the International Conference on Auditory Display (ICAD) 2012.
| PDF | URL | BibTeX
[20] B. Höferlin, R. Netzel, M. Höferlin, D. Weiskopf & G. Heidemann.
Inter-Active Learning of Ad-Hoc Classifiers for Video Visual Analytics.
In IEEE Conference on Visual Analytics Science and Technology (VAST), 2012, pages: 23-32, 2012.
| PDF | DOI | BibTeX
[21] B. Höferlin, H. Pflüger, M. Höferlin, G. Heidemann & D. Weiskopf.
Learning a Visual Attention Model for Adaptive Fast-Forward in Video Surveillance.
In In Proceedings of International Conference on Pattern Recognition Applications and Methods (ICPRAM), 2012 : 25-32, 2012.
| PDF | DOI | BibTeX
[22] J. Moehrmann, S. Bernstein, T. Schlegel, G. Werner & G. Heidemann.
Improving the Usability of Hierarchical Representations for Interactively Labeling Large Image Data Sets.
In Human-Computer Interaction. Design and Development Approaches, 6761 : 618-627, ISBN: 978-3-642-21601-5, 2011. Springer.
| DOI | BibTeX
[23] J. Moehrmann, A. Burkovski, E. Baranovskiy, G.A. Heinze, A. Rapoport & G. Heidemann.
A Discussion on Visual Interactive Data Exploration Using Self-Organizing Maps.
In Proc. 8th Int. Workshop on Advances in Self-Organizing Maps (WSOM 2011), 6731 : 178-187, ISBN: 978-3-642-21565-0, 2011. Springer.
| DOI | BibTeX
[24] R. Borgo, M. Chen, B. Daubney, E. Grundy, G. Heidemann, B. Höferlin, M. Höferlin, H. Jänicke, D. Weiskopf & X. Xie.
A Survey on Video-based Graphics and Video Visualization.
In EG 2011 -- State of the Art Reports, pages: 1-23, 2011. Eurographics Association.
| PDF | BibTeX
[25] S. Brutzer, B. Höferlin & G. Heidemann.
Evaluation of Background Subtraction Techniques for Video Surveillance.
In Computer Vision and Pattern Recognition (CVPR), pages: 1937-1944, 2011. IEEE.
| PDF | DOI | BibTeX
[26] A. Burkovski, S. Klenk & G. Heidemann.
Similarity Calculation with Length Delimiting Dictionary Distance.
In Proc. 23rd IEEE Int. Conf. on Tools with Artificial Intelligence (ICTAI 2011), pages: 856-864, 2011. IEEE.
| DOI | BibTeX
[27] A. Burkovski & G. Heidemann.
Visualization for Coreference Annotation..
In Conference on Recent Advances in Natural Language Processing (RANLP 2011), pages: 692-697, 2011.
| PDF | BibTeX
[28] B. Höferlin, M. Höferlin, M. Raschke, G. Heidemann & D. Weiskopf.
Interactive Auditory Display to Support Situational Awareness in Video Surveillance.
In Proc. Int. Conf. on Auditory Display (ICAD) 2011.
| PDF | URL | BibTeX
[29] M. Höferlin, B. Höferlin, D. Weiskopf & G. Heidemann.
Interactive Schematic Summaries for Exploration of Surveillance Video.
In ACM Int. Conf. on Multimedia Retrieval (ICMR), pages: 9:1-9:8, 2011. ACM.
| PDF | DOI | BibTeX
[30] T. Hartmann, S. Klenk, A. Burkovski & G. Heidemann.
Sentiment Detection with Character n-Grams.
In Proc. 2011 Int. Conf. on Data Mining (DMIN'11), pages: 364-368, 2011.
| PDF | BibTeX
[31] S. Klenk, J. Dippon, P. Fritz & G. Heidemann.
A Personalized Medical Information System.
In Proc. 3rd Workshop on Software Engineering in Health Care (SEHC 2011), pages: 9-12, 2011. ACM.
| PDF | DOI | BibTeX
[32] S. Klenk, P. Fritz, J. Dippon & G. Heidemann.
Medizinisches Data Mining mit dem OCDM System.
In DVMD Jahrestagung 2011 2011.
| BibTeX
[33] S. Klenk, J. Moehrmann, A. Burkovski, J. Dippon, P. Fritz & G. Heidemann.
A Personalized Health Information System to foster Preventive Medicine.
In Proc. 12th Int. Conf. on Bioinformatics \& Computational Biology (BIOCOMP'11), pages: 434-438, 2011. CSREA Press.
| PDF | BibTeX
[34] J. Moehrmann & G. Heidemann.
Automatic Trajectory Clustering for Generating Ground Truth Data Sets.
In Image Processing: Machine Vision Applications III, 7538 (1) : 753808-1-753808-9, 2010. SPIE.
| PDF | BibTeX
[35] S. Klenk, J. Dippon, P. Fritz & G. Heidemann.
Determining Patient Similarity in Medical Social Networks.
In Proc. the First International Workshop on Web Science and Information Exchange in the Medical Web (MedEx 2010), pages: 6-13, 2010.
| PDF | BibTeX
[36] H. Kobdani, H. Schütze, A. Burkovski, S.W. Kessler & G. Heidemann.
Relational Feature Engineering of Natural Language Processing.
In Proc. 19th ACM Conf. on Information and Knowledge Management, CIKM 2010, pages: 1705-1708, 2010.
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[37] J. Moehrmann, G. Heidemann, O. Siemoneit, C. Hubig, U.P. Kaeppeler & P. Levi.
Context Generation with Image Based Sensors: An Interdisciplinary Enquiry on Technical and Social Issues and their Implications for System Design.
In Proc. World Academy of Science, Engineering and Technology, 61 : 311-317, 2010. WASET.
| PDF | BibTeX
[38] J. Moehrmann, X. Wang & G. Heidemann.
Motion Based Situation Recognition in Group Meetings.
In Image Processing: Machine Vision Applications III, 7538 (1) : 75380N-1-75380N-9, 2010. SPIE.
| PDF | BibTeX
[39] J. Rocholl, S. Klenk & G. Heidemann.
Robust 1D Barcode Recognition on Mobile Devices.
In Proc. 20th Int. Conf. on Pattern Recognition (ICPR10), pages: 2712-2715, 2010.
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[40] L. Shoukry, S. Klenk & G. Heidemann.
MPEG-7 Feature Visualization for CBIR Systems.
In Proc. Int. Conf. on Computer Theory and Applications (ICCTA 2010), pages: 86-90, 2010.
| PDF | BibTeX
[41] S. Klenk, J. Dippon, P. Fritz & G. Heidemann.
Relevance Based Visualization of Large Cancer Patient Populations.
In Proc. 1st ACM Int. Health Informatics Symposium (IHI 2010), pages: 275-281, 2010.
| PDF | DOI | BibTeX
[42] B. Höferlin & G. Heidemann.
Selection of an Optimal Set of Discriminative and Robust Local Features with Application to Traffic Sign Recognition.
In Proc. WSCG 2010, 18th Int. Conf. in Central Europe on Computer Graphics, Visualization and Computer Vision, 18 : 9-16, 2010.
| PDF | BibTeX
[43] S. Klenk & G. Heidemann.
A Sparse Coding Based Similarity Measure.
In Proc. 5th Int. Conf. on Data Mining (DMIN'09), pages: 512-516, 2009.
| PDF | BibTeX
[44] S. Klenk, D. Thom & G. Heidemann.
The Normalized Compression Distance as a Distance Measure in Entity Identification.
In Advances in Data Mining: 9th Industrial Conf. on Data Mining ICDM 2009, pages: 325-337, 2009. Springer.
| DOI | BibTeX
[45] J. Imo, S. Klenk & G. Heidemann.
Visualization of Color and Texture Features.
In Proc. 1st ACM Int. Workshop on Super-Visualization (IWSV 08) 2008.
| PDF | BibTeX
[46] B. Kaiser & G. Heidemann.
A Spatio-Temporal Extension of the SUSAN-Filter.
In Proc. 18th Int. Conf. on Artificial Neural Networks ICANN 08, I : 867-876, ISBN: 978-3-540-87535-2, 2008.
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[47] S. Klenk & G. Heidemann.
A New Method for Principal Component Analysis of High-Dimensional Data Using Compressive Sensing.
In Proc. 4th Int. Conf. on Data Mining DMIN 08, pages: 191-196, 2008.
| PDF | BibTeX
[48] B. Kaiser & G. Heidemann.
Qualitative Analysis of Spatio-Temporal Event Detectors.
In Proc. 19th Int. Conf. on Pattern Recognition ICPR 08 2008. IEEE.(CFP08182)
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[49] G. Heidemann & H. Ritter.
Compression for Visual Pattern Recognition.
In Proc. 3rd IEEE Int. Symp. on Communications, Control and Signal Processing, pages: 1520-1523, 2008. IEEE.
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[50] G. Heidemann & H. Ritter.
On the Contribution of Compression to Visual Pattern Recognition.
In Proc. 3rd Int. Conf. on Comp. Vision Theory and Applications, 2 : 83-89, 2008.
| PDF | URL | BibTeX
[51] J. Imo, S. Klenk & G. Heidemann.
Interactive Feature Visualization for Image Retrieval.
In Proc. 19th Int. Conf. on Pattern Recognition ICPR 08 2008. IEEE.(CFP08182)
| PDF | DOI | BibTeX
[52] B. Kaiser & G. Heidemann.
Context-Free Detection of Events.
In Proc. 15th Scandinavian Conference on Image Analysis SCIA 07, pages: 223-232, 2007.
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[53] G. Heidemann & S. Klenk.
Visual Analytics for Image Retrieval.
In Proc. 17th Workshop Computational Intelligence, pages: 15-24, 2007.
| PDF | BibTeX
[54] M. Schöpfer, G. Heidemann & H. Ritter.
Acquisition and Application of a Tactile Database.
In Proc. IEEE Int. Conf. on Robotics and Automation ICRA 07, pages: 1517-1522, 2007.
| DOI | BibTeX
[55] G. Heidemann.
Color Symmetry for Interest Point Detection.
In 12. Workshop Farbbildverarbeitung, pages: 5-13, 2006. Schriftenreihe des Zentrums f\.
| BibTeX
[56] H. Bekel, G. Heidemann & H. Ritter.
SOM Based Image Data Structuring in an Augmented Reality Scenario.
In Proc. IEEE Int'l Joint Conf. on Neural Networks IJCNN 05, pages: 3278-3283, 2005.
| DOI | BibTeX
[57] I. Bax, G. Heidemann & H. Ritter.
A Hierarchical Feedforward Network for Object Detection Tasks.
In Proc. SPIE Conf. onIndependent Component Analyses, Wavelets, Unsupervised Smart Sensors, Neural Networks, 5818 : 144-152, 2005.
| PDF | DOI | BibTeX
[58] I. Bax, G. Heidemann & H. Ritter.
Face Detection and Identification Using a Hierarchical Feed-forward Recognition Architecture.
In Proc. IEEE Int. Joint Conf. on Neural Networks IJCNN 05, pages: 1675-1680, 2005.
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[59] I. Bax, G. Heidemann & H. Ritter.
Using Non-negative Sparse Profiles in a Hierarchical Feature Extraction Network.
In Proc. 9th IAPR Conf. Machine Vision Applications MVA 05, pages: 464-467, 2005.
| PDF | BibTeX
[60] G. Heidemann & M. Schöpfer.
Dynamic Tactile Sensing for Object Identification.
In Proc. IEEE Int. Conf. Robotics and Automation ICRA 04, pages: 813-818, 2004. IEEE.
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[61] G. Heidemann, H. Bekel, I. Bax & A. Saalbach.
Hand Gesture Recognition: Self-Organising Maps as a Graphical User Interface for the Partitioning of Large Training Data Sets.
In Proc. Int. Conf. on Pattern Recognition ICPR 04, 4 : 487-490, 2004. IEEE-CS.
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[62] H. Bekel, I. Bax, G. Heidemann & H. Ritter.
Adaptive Computer Vision: Online Learning for Object Recognition.
In Proc. DAGM 2004, pages: 447-454, 2004. Springer.
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[63] G. Heidemann, I. Bax, H. Bekel, C. Bauckhage, S. Wachsmuth, G. Fink, A. Pinz, H. Ritter & G. Sagerer.
Multimodal Interaction in an Augmented Reality Scenario.
In Proc. Int. Conf. Multimodal Interfaces ICMI 04, pages: 53-60, 2004. ACM Press.
| PDF | DOI | BibTeX
[64] G. Heidemann, H. Bekel, I. Bax & H. Ritter.
Interactive Online Learning.
In Proc. PRIA 2004, pages: 44-48, 2004.
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[65] I. Bax, H. Bekel & G. Heidemann.
Recognition of Gestural Object Reference with Auditory Feedback.
In Proc. Int. Conf. Neural Networks ICANN 03, pages: 425-432, 2003.
| PDF | DOI | BibTeX
[66] G. Heidemann, R. Rae, H. Bekel, I. Bax & H. Ritter.
Integrating Context-Free and Context-Dependent Attentional Mechanisms for Gestural Object Reference.
In Proc. IEEE Int. Conf. Cognitive Vision Systems, pages: 22-33, 2003.
| PDF | DOI | BibTeX
[67] G. Heidemann, A. Saalbach & H. Ritter.
Semi-Automatic Acquisition and Labeling of Image Data Using SOMs.
In Proc. ESANN 03, pages: 503-508, ISBN: 2-930307-03-X, 2003. d-side publications.
| PDF | BibTeX
[68] A. Saalbach, G. Heidemann & H. Ritter.
Representing Object Manifolds by Parametrized SOMs.
In Proc. Int. Conf. on Pattern Recognition ICPR 02, pages: 184-187, 2002. IEEE-CS.
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[69] A. Saalbach, G. Heidemann & H. Ritter.
Parametrized SOMs for Object Recognition and Pose Estimation.
In Proc. Int. Conf. on Artificial Neural Networks ICANN 02, pages: 902-907, 2002. Springer.
| PDF | DOI | BibTeX
[70] G. Heidemann & H. Ritter.
Combining Gestural and Contact Information for Visual Guidance of Multi-Finger Grasps.
In Proc. ESANN 02, pages: 301-306, ISBN: 2-930307-02, 2002. d-side publications.
| PDF | BibTeX
[71] G. Sagerer, C. Bauckhage, E. Braun, G. Heidemann, F. Kummert, H. Ritter & D. Schlüter.
Integrating Recognition Paradigms in a Multiple-path Architecture.
In Proc. Int'l Conf. on Advances in Pattern Recognition (ICAPR), pages: 202-211, 2001. Springer.
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[72] G. Heidemann & H. Ritter.
Visual Checking of Grasping Positions of a Three-Fingered Robot Hand.
In Proc. Int'l Conf. on Artificial Neural Networks ICANN 01, pages: 891-898, 2001. Springer.
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[73] G. Heidemann.
A Multi-Purpose Visual Classification System.
In Proc. 7th Fuzzy Days, Dortmund, 2001, pages: 305-312, 2001. Springer.
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[74] J. Steil, G. Heidemann, J. Jockusch, R. Rae, N. Jungclaus & H. Ritter.
Guiding Attention for Grasping Tasks by Gestural Instruction: The GRAVIS-Robot Architecture.
In Proc. IEEE Int'l Conf. on Intelligent Robots and Systems IROS 01, pages: 1570-1577, 2001.
| PDF | DOI | BibTeX
[75] G. Heidemann, D. Lücke & H. Ritter.
Segmentation of Partially Occluded Objects by Local Classification.
In Proc. IEEE-INNS-ENNS Int'l Joint Conf. on Neural Networks IJCNN 2000, I : 152-157, 2000. IEEE.
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[76] G. Heidemann, D. Lücke & H. Ritter.
A System for Various Visual Classification Tasks Based on Neural Networks.
In Proc. 15th Int'l Conf. on Pattern Recognition ICPR 2000, Barcelona, I : 9-12, 2000. IEEE-CS.
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[77] G. Heidemann & H. Ritter.
Combining Multiple Neural Nets for Visual Feature Selection and Classification.
In Proc. 9th Int'l Conf. on Artificial Neural Networks ICANN 99, pages: 365-370, 1999. IEE.
| PDF | DOI | BibTeX
[78] G. Heidemann & H. Ritter.
Hybride Objekterkennung: Konstruktion einer Zwischenrepräsentation für den Übergang von holistischer zu semantischer Erkennung.
In Proc. 4. Fachtagung der Gesellschaft für Kognitionswissenschaft KogWiss 99, pages: 290-291, 1999.
| PDF | BibTeX
[79] G. Heidemann, T.W. Nattkemper & H. Ritter.
Farbe und Symmetrie für die datengetriebene Generierung prägnanter Fokuspunkte.
In Proc. 4. Workshop Farbbildverarbeitung, pages: 65-71, 1998. F\.
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[80] G. Heidemann, F. Kummert, H. Ritter & G. Sagerer.
A Hybrid Object Recognition Architecture.
In Proc. Int. Conf. on Artificial Neural Networks ICANN 96, pages: 305-310, 1996. Springer.
| PDF | DOI | BibTeX
[81] G. Heidemann & H. Ritter.
A Neural 3-D Object Recognition Architecture Using Optimized Gabor Filters.
In Proc. 13th Int. Conf. on Pattern Recognition ICPR 96, IV : 70-74, 1996. IEEE-CS.
| PDF | DOI | BibTeX
[82] G. Heidemann & H. Ritter.
A Neural Recognition Architecture for Composed Objects.
In Proc. 18. DAGM-Symp., pages: 475-482, 1996. Springer.
| PDF | DOI | BibTeX
[83] G. Heidemann, T. Nattkemper, G. Menkhaus & H. Ritter.
Blicksteuerung durch präattentive Fokussierungspunkte.
In Proc. in Artificial Intelligence, pages: 109-116, 1996.
| PDF | URL | BibTeX
[84] R. Moratz, G. Heidemann, S. Posch, H. Ritter & G. Sagerer.
Representing Procedural Knowledge for Semantic Networks Using Neural Nets.
In Proc. 9th Scandinavian Conf. on Image Analysis SCIA 95, pages: 819-828, 1995.
| PDF | URL | BibTeX

Book Chapters

[1] J. Schöning & G. Heidemann.
Evaluation of Multi-view 3D Reconstruction Software.
In Computer Analysis of Images and Patterns, 9257 : 450-461, ISBN: 978-3-319-23116-7, 2015. Springer International Publishing.
| PDF | DOI | BibTeX
[2] A. Burkovski, W. Kessler, G. Heidemann, H. Kobdani & H. Schütze.
Self organizing maps in NLP: exploration of coreference feature space.
In Advances in Self-Organizing Maps, pages: 228-237, ISBN: 978-3-642-21565-0, 2011. Springer.
| DOI | BibTeX
[3] G. Heidemann & H. Ritter.
Data Compression --- a Generic Principle of Pattern Recognition?.
In Computer Vision and Computer Graphics. Theory and Applications, 24 : 202-212, ISBN: 978-3-642-10225-7, 2009. Springer.
| PDF | DOI | BibTeX
[4] G. Heidemann & H. Ritter.
Making Robots Learn to See.
In Perspectives on Adaptivity and Learning, pages: 285-309, ISBN: 978-3-642-05510-2, 2003. Springer.
| PDF | DOI | BibTeX
[5] G. Heidemann.
Semi-Automatic Acquisition of Visual Knowledge.
In Einsatz von Fuzzy Sets, Neuronalen Netzen und Künstlicher Intelligenz in industrieller Produktion und Umweltforschungpages: 1-14, 2003. VDI-Verlag.
| PDF | BibTeX

Habilitations

[1] G. Heidemann.
Interest Point Detection: Algorithms, Evaluation, and Application.
Habilitation, Univ.Bielefeld, Technische Fakultät, 2005.
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Dissertations

[1] J. Moehrmann.
Effiziente Erstellung aufgabenspezifischer Bilderkennungssysteme.
PhD thesis, Universität Osnabrück, Institute of Cognitive Science, 2014.
| URL | BibTeX
[2] B. Höferlin.
Scalable Visual Analytics for Video Surveillance.
PhD thesis, Universität Stuttgart, Institut für Visualisierung und Interaktive Systeme (VIS), ISBN: 978-3843914918, 2013.
| URL | BibTeX
[3] M.P. Schöpfer.
Tactile Perception of Cognitive Robots.
PhD thesis, Univ. Bielefeld, Technische Fakultät, 2012.
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[4] H. Bekel.
Die Brille mit Gedächtnis.
PhD thesis, Univ. Bielefeld, Technische Fakultät, 2010.
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[5] I. Bax.
Hierarchical Feed-Forward Models for Robust Object Recognition.
PhD thesis, Univ. Bielefeld, Technische Fakultät, 2007.
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[6] G. Heidemann.
Ein flexibel einsetzbares Objekterkennungssystem auf der Basis neuronaler Netze (A multiple-task object recognition system based on neural networks).
PhD thesis, Univ. Bielefeld, Technische Fakultät, ISBN: 3-89601-190-1, 1998.(Infix, DISKI 190)
| URL | BibTeX

Student Papers, Diploma, Master-/Bachelor-Thesises, etc.

[1] T. Conrady.
Evaluation of Blur Detection Algorithms for Object of Interest.
Bachelor Thesis, Univ. Osnabrück, 2016.
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[2] L. Edelkott.
Adaptive K-Means Clustering of Data Sequences -- Clustering of video sequences with dynamic cluster count and recognition of their serial identity.
Bachelor Thesis, Univ. Osnabrück, 2016.
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[3] R. Frank.
Evaluating Weakly Supervised Semiautomatic Object Recognition with a Random Forest Classifier.
Bachelor Thesis, Univ. Osnabrück, 2015.
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[4] C.O. Gutknecht.
Technische und benutzerspezifische Analyse der Einsatz- und Verbreitungsmöglichkeiten eines flexiblen Bilderkennungssystems.
Bachelor Thesis, Univ. Osnabrück, 2014.
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[5] A. Schaffland.
Multimodal Image Classification.
Bachelor Thesis, Univ. Osnabrück, 2013.
| BibTeX
[6] J. Schleith.
Interactive Clustering \& Advanced User.
Bachelor Thesis, Univ. Osnabrück, 2013.
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[7] A. Tonn.
Detection and Prediction of Relevant Image Areas for Efficient Image Annotation.
Bachelor Thesis, Univ. Osnabrück, 2013.
| BibTeX
[8] A. Györkös.
Erkennung von Aktivitäten mit Hilfe mobiler Geräte.
Studienarbeit, Univ. Stuttgart, 2011.
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[9] J. Liu.
Scene-Adaptive Trajectory Extractio from Videos.
Masterarbeit, Univ. Stuttgart, 2011.
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[10] E. Baranovskiy, G.A. Heinze & A. Rapoport.
Untersuchung von Frameworks für Self Organizing Maps.
Fachstudie, Univ. Stuttgart, 2011.
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[11] B. Goloubets.
Sonifikation von Überwachungssequenzen unter Berücksichtigung der Psychoakustik.
Diplomarbeit, Univ. Stuttgart, 2011.
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[12] S. Stock.
Eine untersuchung von BLNs als Umgebungsrepräsentation für wissensbasierte Roboter.
Masterarbeit, Univ. Osnabrück, 2011.
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[13] T. Comes.
Fuzzy-linguistisches Modell zur Klassifikation von Kundenmeinungen.
Masterarbeit, Univ. Hohenheim, 2011.
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[14] D. Tsendragchaa.
Hintergrundsubtraktion mit PTZ-Kameras.
Diplomarbeit, Univ. Stuttgart, 2011.
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[15] C. Keller.
Theoretical and Practical Perspectives on Ontology Learning from Folksonomies.
Diplomarbeit, Univ. Stuttgart, 2010.
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[16] S.W. Kessler.
Analysis and Visualization of Coreference Features.
Diplomarbeit, Univ. Stuttgart, 2010.
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[17] E.D. Klenske.
Textvisualisierung zur Koreferenzerkennung.
Studienarbeit, Univ. Stuttgart, 2010.
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[18] S. Lanig, M. Lemcke & P. Mayer.
Evaluation von Data Mining Werkzeugen.
Fachstudie, Univ. Stuttgart, 2010.
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[19] G. Latuske, J. Räuchle & N. Röhle.
Untersuchung intelligenter Videoüberwachungssysteme.
Fachstudie, Univ. Stuttgart, 2010.
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[20] B. Globoulets.
Sonifizierung von Videoüberwachungsdaten.
Studienarbeit, Univ. Stuttgart, 2010.
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[21] T. Müller.
Adressing the Puntuation Marks Problem in Automatic Handwriting Recognition.
Studienarbeit, Univ. Stuttgart, 2010.
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[22] A. Mahmoud.
Machine Learning in Physical Cryptography.
Masterarbeit, Univ. Stuttgart, 2010.
| BibTeX
[23] R. Netzel.
Bewegungserkennung mit Hilfe von Rechteckmerkmalen.
Studienarbeit, Univ. Stuttgart, 2010.
| BibTeX
[24] H. Pflüger.
Berechnung eines Aufmerksamkeitsmodells aus Videodaten mittels Rechteckmerkmalen.
Studienarbeit, Univ. Stuttgart, 2010.
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[25] J.J. Sanz Martin.
Recognition of Motion Patterns based on Mobile Device Sensor Data.
Masterarbeit, Univ. Stuttgart, 2010.
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[26] D. Beck.
Design and Prototypical Implementation of a Linguistic Search Engine.
Diplomarbeit, Univ. Stuttgart, 2010.
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[27] P. Gründer.
Analyse komressionsbasierter Ähnlichkeitsmetrik für mehrdimensionale Objekte.
Studienarbeit, Univ. Stuttgart, 2010.
| BibTeX
[28] J.S. Selim.
Semi-Automatic Labeling of Mobile Device Sensor Data.
Bachelor Thesis, Univ. Stuttgart / German Univ. in Cairo, 2010.
| BibTeX
[29] S. Brutzer.
Kompressionsbasierte Mustererkennung auf Bildern.
Diplomarbeit, Univ. Stuttgart, 2010.
| BibTeX
[30] D. Thom.
Kompressionsbasierte Mustererkennung auf Bildern.
Diplomarbeit, Univ. Stuttgart, 2010.
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[31] M. Gabb.
Hierarchiche Klassifikation von Fahrzeugen.
Diplomarbeit, Univ. Stuttgart, 2010.
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[32] T. Hartmann.
Erzeugung und Anwendung von kontextuellen Wörterbüchern.
Studienarbeit, Univ. Stuttgart, 2010.
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[33] A. Tyaneva.
Development of a Two Layer Classification System for Situations in Meetings.
Diplomarbeit, Univ. Stuttgart, 2010.
| BibTeX
[34] F. Häuser.
Visualisierung von MPEG-7-Merkmalen in der Bildverarbeitung.
Diplomarbeit, Univ. Stuttgart, 2009.
| BibTeX
[35] S. Brutzer.
Evaluations of Methods for Left Luggage Detection in Video Data.
Studienarbeit, Univ. Stuttgart, 2009.
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[36] F. Pachner.
Fahrwerksoptimierung mittels künstlicher Intelligenz.
Diplomarbeit, Univ. Stuttgart, 2009.
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[37] A. Burkowski.
Analyse und Visualisierung von NCD-Features.
Diplomarbeit, Univ. Stuttgart, 2009.
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[38] J.C. Rocholl.
Robust 1D Barcode Recognition on Mobile Devices.
Diplomarbeit, Univ. Stuttgart, 2009.
| BibTeX
[39] C. Keller.
Intelligente E-Learning Systeme.
Studienarbeit, Univ. Stuttgart, 2009.
| BibTeX
[40] S. Bertele.
Implementierung von Algorithmen zur Merkmalsextraktion für Objekterkennung in der Sensordatenverarbeitung und Datenfusion für ein Umgebungsmodell.
Studienarbeit, Univ. Stuttgart, 2009.
| BibTeX
[41] X. Wang.
Interaktionserkennung in Videodaten.
Diplomarbeit, Univ. Stuttgart, 2009.
| BibTeX
[42] Y. Wang.
Entwicklung von Verfahren zur Personenerkennung und -verfolgung in Videodaten.
Studienarbeit, Univ. Stuttgart, 2009.
| BibTeX
[43] J. Wunschik.
SVN-basierte Analyse von Open-Source-Softwareprojekten zur Bewertung von Projektivität.
Diplomarbeit, Univ. Stuttgart, 2009.
| BibTeX
[44] L.H. Shoukry.
MPEG-7 Feature Visualization for CBIR Systems.
Bachelor Thesis, Univ. Stuttgart / German Univ. in Cairo, 2008.
| BibTeX
[45] B. Höferlin.
Verkehrszeichenerkennung.
Diplomarbeit, Univ. Stuttgart, 2008.
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[46] L.C. Depold.
Evaluierung von Systemen zur Wissensrepräsentation mit Anwendung in der Objekterkennung.
Studienarbeit, Univ. Stuttgart, 2008.
| BibTeX
[47] D. Thom.
Visualisierung von Mustern kompressionsbasierter Ähnlichkeitsmetriken.
Studienarbeit, Univ. Stuttgart, 2008.
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[48] A.G. Lorenzo.
Bandwidth Extension of Throat Microphone Signals with Feature Mapping Techniques.
Diplomarbeit, Univ. Stuttgart, 2008.
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[49] I. Hildebrandt.
Entwicklung eines semantischen Nachrichtensystems für die Produktionsüberwachung und -steuerung.
Diplomarbeit, Univ. Stuttgart, 2008.
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[50] H. Hilkert.
Entwicklung eines Online-Planspiels zum Szenario ''Engineering einer Gepäckförderanlage für einen Großflughafen''.
Diplomarbeit, Univ. Stuttgart, 2008.
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[51] P. Schaffroth.
Analyse elementarer Ereignisse in Videodaten.
Studienarbeit, Univ. Stuttgart, 2008.
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[52] B. Mrsic.
Analyse elementarer Ereignisse in Videodaten.
Diplomarbeit, Univ. Stuttgart, 2008.
| BibTeX
[53] J. Imo.
Visualisierung von Farbhistogrammen und Farbtexturmerkmalen zur Anwendung in CBIR-Systemen.
Diplomarbeit, Univ. Stuttgart, 2008.
| BibTeX
[54] E. Woldesemayat.
Agentenorientiertes Konzept für das Energiemanagement in Wohngebäuden.
Diplomarbeit, Univ. Stuttgart, 2007.
| BibTeX
[55] H. Wolf.
Smarte Philosophen -- Modell zur intelligenten Zuweisung von Diensten in Umgebungen ubiquitärer Datenverarbeitung.
Studienarbeit, Univ. Stuttgart, 2007.
| BibTeX
[56] L.E.T. Amissah.
Entwicklung einer Software zur Anwendung DGA-basierter Interpretationsschemata.
Diplomarbeit, Univ. Stuttgart, 2007.
| BibTeX
[57] B. Kaiser.
Detektion von raum-zeitlichen Interest Points in Bildsequenzen.
Diplomarbeit, Univ. Bielefeld, 2005.
| BibTeX
[58] G. Heidemann.
Interest Point Detection: Algorithms, Evaluation, and Application.
Habilitation, Univ.Bielefeld, Technische Fakultät, 2005.
| BibTeX
[59] F. Benites.
Categorization of Image Databases.
Diplomarbeit, Univ. Bielefeld, 2005.
| BibTeX
[60] M.P. Schöpfer.
Akquisition und Klassifikation taktiler Objektdaten.
Diplomarbeit, Univ. Bielefeld, 2004.
| BibTeX
[61] D. Brün.
Aufbau und Ansteuerung eines Stereo-Vision-Systems.
Diplomarbeit, Univ. Bielefeld, 2001.
| BibTeX
[62] A. Saalbach.
Self-Organizing Maps zur halbautomatischen Erzeugung datennaher Klasseneinteilungen.
Diplomarbeit, Univ. Bielefeld, 2001.
| BibTeX
[63] C. Strauss.
Farbbasiertes Template Matching unter Verwendung synthetischer Templates.
Diplomarbeit, Univ. Bielefeld, 2000.
| BibTeX
[64] D. Strotmann.
Lokale Klassifikation als Basis für die Erkennung teilverdeckter Objekte.
Diplomarbeit, Univ. Bielefeld, 1999.
| BibTeX
[65] G. Menkhaus.
Präattentive Fokussierungspunktgenerierung zur Objekterkennung mit künstlichen neuronalen Netzen.
Diplomarbeit, Univ. Bielefeld, 1997.
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[66] C. Bahlmann.
Künstliche Neuronale Netze zur optischen Qualitätskontrolle textiler Nähte.
Diplomarbeit, Univ. Bielefeld, 1997.
| BibTeX
[67] T.W. Nattkemper.
Untersuchung und Erweiterung eines Ansatzes zur modellfreien Aufmerksamkeitssteuerung durch lokale Symmetrien in einem Computer Vision System.
Diplomarbeit, Univ. Bielefeld, 1997.
| BibTeX
[68] B. Büsing.
Objektklassifikation von teilverdeckten Objekten mit neuronalen Netzen.
Diplomarbeit, Univ. Bielefeld, 1997.
| BibTeX
[69] K. Thierfeldt.
Generierung rezeptiver Felder zur neuronalen Objekterkennung.
Diplomarbeit, Univ. Bielefeld, 1995.
| BibTeX
[70] G. Heidemann.
Konkurrenz oszillierender und strukturierter Domänen in einem Aktivator-Inhibitor System (Competition of Oscillating and Structured Domains in an Activator-Inhibitor System).
Diplomarbeit, Univ. Karlsruhe, 1992.
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