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| Issue Date | Title | Author(s) |
| 2019 | A very concise feature representation for time series classification understanding | Tanisaro, P.; Heidemann, G. |
| 2018 | An empirical study on bidirectional recurrent neural networks for human motion recognition | Tanisaro, P.; Heidemann, G. |
| 2022 | An Image Based Object Recognition System for Wound Detection and Classification of Diabetic Foot and Venous Leg Ulcers | Hüsers, J.; Moelleken, M.; Richter, M.L.; Przysucha, M.; Malihi, L.; Busch, D.; Götz, N.-A.; Heggemann, J.; Hafer, G.; Wiemeyer, S.; Babitsch, B. ; Heidemann, G. ; Dissemond, J.; Erfurt-Berge, C.; Hübner, U. |
| 2019 | An interactive web application for the creation, organization, and visualization of repeat photographs | Schaffland, A.; Vornberger, O. ; Heidemann, G. |
| 2022 | Automatic Wound Type Classification with Convolutional Neural Networks | Malihi, L.; Hüsers, J.; Richter, M.L.; Moelleken, M.; Przysucha, M.; Busch, D.; Heggemann, J.; Hafer, G.; Wiemeyer, S.; Heidemann, G. ; Dissemond, J.; Erfurt-Berge, C.; Hübner, U. |
| 2017 | Bio-inspired architecture for deriving 3D models from video sequences | Schöning, J. ; Heidemann, G. |
| 2023 | Can Synthetic Images Improve CNN Performance in Wound Image Classification? | Malihi, Leila; Hübner, Ursula; Richter, Mats L.; Moelleken, Maurice; Przysucha, Mareike; Busch, Dorothee; Heggemann, Jan; Hafer, Guido; Wiemeyer, Stefan; Heidemann, Gunther ; Dissemond, Joachim; Erfurt-Berge, Cornelia; Barkhau, Carlotta; Hendriks, Achim; Hüsers, Jens |
| 2017 | Classifying bio-inspired model of point-light human motion using Echo State networks | Tanisaro, P.; Lehman, C.; Sütfeld, L.; Pipa, G. ; Heidemann, G. |
| 2017 | Content-aware 3D reconstruction with gaze data | Schoning, J. ; Jiang, X.; Menon, C.; Heidemann, G. |
| 2016 | CORVIDAE: Coreference resolution visual development & analysis environment | Möller, N.; Heidemann, G. |
| 2019 | Dimensionality Reduction for Visualization of Time Series and Trajectories | Tanisaro, P.; Heidemann, G. |
| 2023 | Efficient and Controllable Model Compression through Sequential Knowledge Distillation and Pruning | Malihi, Leila; Heidemann, Gunther |
| 2012 | Efficient annotation of image data sets for computer vision applications | Moehrmann, J.; Heidemann, G. |
| 2013 | Efficient development of user-defined image recognition systems | Moehrmann, J.; Heidemann, G. |
| 2021 | Embedding semantic relationships in hidden representations via label smoothing | Marino, Michael; Nieters, Pascal ; Heidemann, Gunther ; Hertzberg, Joachim |
| 2012 | Evaluation of Fast-Forward Video Visualization | Hoeferlin, Markus; Kurzhals, Kuno; Hoeferlin, Benjamin; Heidemann, Gunther ; Weiskopf, Daniel |
| 2015 | Evaluation of multi-view 3D reconstruction software | Schöning, J. ; Heidemann, G. |
| 2017 | Exploratory multimodal data analysis with standard multimedia player multimedia containers: A feasible solution to make multimodal research data accessible to the broad audience | Schöning, J. ; Gert, A.L.; Acik, A. ; Kietzmann, T.C.; Heidemann, G. ; König, P. |
| 2017 | Eye tracking data in multimedia containers for instantaneous visualizations | Schöning, J. ; Faion, P.; Heidemann, G. ; Krumnack, U. |
| 2015 | FOREST: A flexible object recognition system | Moehrmann, J.; Heidemann, G. |
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