| Realtime ray tracing for current and future games J Schmittler, D Pohl, T Dahmen, C Vogelgesang, P Slusallek ACM SIGGRAPH 2005 Courses, 23-es, 2005 | 41 | 2005 |
| Feature adaptive sampling for scanning electron microscopy T Dahmen, M Engstler, C Pauly, P Trampert, N De Jonge, F Mücklich, ... Scientific reports 6 (1), 25350, 2016 | 39 | 2016 |
| How should a fixed budget of dwell time be spent in scanning electron microscopy to optimize image quality? P Trampert, F Bourghorbel, P Potocek, M Peemen, C Schlinkmann, ... Ultramicroscopy 191, 11-17, 2018 | 27 | 2018 |
| Combined scanning transmission electron microscopy tilt-and focal series T Dahmen, JP Baudoin, AR Lupini, C Kübel, P Slusallek, N De Jonge Microscopy and Microanalysis 20 (2), 548-560, 2014 | 27 | 2014 |
| Digital reality: a model-based approach to supervised learning from synthetic data T Dahmen, P Trampert, F Boughorbel, J Sprenger, M Klusch, K Fischer, ... AI Perspectives 1 (1), 1-12, 2019 | 26 | 2019 |
| Applying ray tracing for virtual reality and industrial design I Wald, A Dietrich, C Benthin, A Efremov, T Dahmen, J Gunther, V Havran, ... 2006 IEEE symposium on interactive ray tracing, 177-185, 2006 | 24 | 2006 |
| An automated workflow for the biomechanical simulation of a tibia with implant using computed tomography and the finite element method T Dahmen, M Roland, T Tjardes, B Bouillon, P Slusallek, S Diebels Computers & Mathematics with Applications 70 (5), 903-916, 2015 | 20 | 2015 |
| Deep neural networks for analysis of microscopy images—synthetic data generation and adaptive sampling P Trampert, D Rubinstein, F Boughorbel, C Schlinkmann, M Luschkova, ... Crystals 11 (3), 258, 2021 | 19 | 2021 |
| Neuroscope: An explainable ai toolbox for semantic segmentation and image classification of convolutional neural nets C Schorr, P Goodarzi, F Chen, T Dahmen Applied Sciences 11 (5), 2199, 2021 | 19 | 2021 |
| Interactive headlight simulation: a case study of interactive distributed ray tracing C Benthin, T Dahmen, I Wald, P Slusallek ACM International Conference Proceeding Series 29, 83-88, 2002 | 18 | 2002 |
| The Ettention software package T Dahmen, L Marsalek, N Marniok, B Turoňová, S Bogachev, P Trampert, ... Ultramicroscopy 161, 110-118, 2016 | 17 | 2016 |
| Interactive Headlight Simulation–A Case Study of Distributed Interactive Ray Tracing C Benthin, I Wald, T Dahmen, P Slusallek Proceedings of the 4th Eurographics Workshop on Parallel Graphics and …, 2002 | 14 | 2002 |
| Exemplar-based inpainting as a solution to the missing wedge problem in electron tomography P Trampert, W Wang, D Chen, RBG Ravelli, T Dahmen, PJ Peters, ... Ultramicroscopy 191, 1-10, 2018 | 12 | 2018 |
| Linear chains of HER2 receptors found in the plasma membrane using liquid-phase electron microscopy K Parker, P Trampert, V Tinnemann, D Peckys, T Dahmen, N de Jonge Biophysical Journal 115 (3), 503-513, 2018 | 11 | 2018 |
| Synthetic training data generation for deep learning based quality inspection P Gutierrez, M Luschkova, A Cordier, M Shukor, M Schappert, T Dahmen Fifteenth International Conference on Quality Control by Artificial Vision …, 2021 | 10 | 2021 |
| Exemplar-based inpainting based on dictionary learning for sparse scanning electron microscopy P Trampert, S Schlabach, T Dahmen, P Slusallek Microscopy and Microanalysis 24 (S1), 700-701, 2018 | 10 | 2018 |
| Modelling and characterization of ductile fracture surface in Al-Si alloys by means of Voronoi tessellation A Kruglova, M Roland, S Diebels, T Dahmen, P Slusallek, F Mücklich Materials Characterization 131, 1-11, 2017 | 9 | 2017 |
| Less than full circumferential fusion of a tibial nonunion is sufficient to achieve mechanically valid fusion-Proof of concept using a finite element modeling approach T Tjardes, M Roland, R Otchwemah, T Dahmen, S Diebels, B Bouillon BMC Musculoskeletal Disorders 15, 1-7, 2014 | 9 | 2014 |
| Predicting the adhesion strength of micropatterned surfaces using supervised machine learning M Samri, J Thiemecke, E Prinz, T Dahmen, R Hensel, E Arzt Materials Today 53, 41-50, 2022 | 8 | 2022 |
| Sparse scanning electron microscopy data acquisition and deep neural networks for automated segmentation in connectomics P Potocek, P Trampert, M Peemen, R Schoenmakers, T Dahmen Microscopy and Microanalysis 26 (3), 403-412, 2020 | 8 | 2020 |
Philipp SlusallekProfessor for Computer Graphics, Saarland University & DFKI, Saarland Informatics CampusBestätigte E-Mail-Adresse bei cs.uni-saarland.de
