| Erscheinungsdatum | Titel | Autor(en) |
| 2022 | Heritage and Repeat Photography: Techniques, Management, Applications, and Publications | Schaffland, Axel; Heidemann, Gunther |
| 2020 | Hierarchical Modeling with Neurodynamical Agglomerative Analysis | Marino, M.; Schröter, G.; Heidemann, G. ; Hertzberg, J. |
| 2016 | Image based spare parts reconstruction for repairing vital infrastructure after disasters: Creating or ordering replica of spare parts for overhauling infrastructure | Schoning, J. ; Heidemann, G. |
| 2018 | Image-based 3D Reconstruction: Neural Networks vs. Multiview Geometry | Schöning, J. ; Heidemann, G. |
| 2023 | Individual Recognition in Wild Chimpanzees and Beyond: Supervised Representation Learning | Brima, Yusuf; Southern, Lara; Krumnack, Ulf ; Heidemann, Gunther ; Pika, Simone |
| 2012 | Inter-active learning of ad-hoc classifiers for video visual analytics | Höferlin, B.; Netzel, R.; Höferlin, M.; Weiskopf, D.; Heidemann, G. |
| 2015 | Interactive 3D modeling a survey-based perspective on interactive 3D reconstruction | Schöming, J.; Heidemann, G. |
| 2016 | Interactive feature growing for accurate object detection in megapixel images | Schöning, J. ; Faion, P.; Heidemann, G. |
| 2013 | Interactive Schematic Summaries for Faceted Exploration of Surveillance Video | Hoeferlin, Markus; Hoeferlin, Benjamin; Heidemann, Gunther ; Weiskopf, Daniel |
| 2023 | Investigating Pre-trained Language Models on Cross-Domain Datasets, a Step Closer to General AI | Ballout, Mohamad; Krumnack, Ulf ; Heidemann, Gunther ; Kühnberger, Kai-Uwe |
| 2012 | Learning a visual attention model for adaptive fast-forward in video surveillance | Ḧoferlin, B.; Pfl̈uger, H.; Ḧoferlin, M.; Heidemann, G. ; Weiskopf, D. |
| 2020 | New Interactive Methods for Image Registration with Applications in Repeat Photography | Schaffland, A.; Bui, T.H.; Vornberger, O. ; Heidemann, G. |
| 2018 | Object of Interest Segmentation in Video Sequences with Gaze Data | Krieger, L.; Heidemann, G. ; Schöning, J. |
| 2023 | Opening theBlack Box: Analyzing Attention Weights andHidden States inPre-trained Language Models forNon-language Tasks | Ballout, Mohamad; Krumnack, Ulf ; Heidemann, Gunther ; Kühnberger, Kai-Uwe |
| 2016 | Pixel-wise ground truth annotation in videos: An semi-automatic approach for pixel-wise and semantic object annotation | Schöning, J. ; Faion, P.; Heidemann, G. |
| 2017 | Providing video annotations in multimedia containers for visualization and research | Schoning, J. ; Faion, P.; Heidemann, G. ; Krumnack, U. |
| 2017 | Quasi view-independent human motion recognition in subspaces | Tanisaro, P.; Mahner, F.; Heidemann, G. |
| 2012 | Redundant dictionary spaces as a general concept for the analysis of non-vectorial data | Klenk, S.; Dippon, J.; Burkovski, A.; Heidemann, G. |
| 2015 | Scalable video visual analytics | Hoeferlin, Benjamin; Hoeferlin, Markus; Heidemann, Gunther ; Weiskopf, Daniel |
| 2015 | Semi-automatic ground truth annotation in videos: An interactive tool for polygon-based object annotation and segmentation | Schöning, J. ; Faion, P.; Heidemann, G. |
HOCHSCHULBIBLIOGRAPHIE