| Texture Fields: Learning Texture Representations in Function Space M Oechsle, L Mescheder, M Niemeyer, T Strauss, A Geiger Proceedings of the IEEE International Conference on Computer Vision, 4531-4540, 2019 | 342 | 2019 |
| CANet: An unsupervised intrusion detection system for high dimensional CAN bus data M Hanselmann, T Strauss, K Dormann, H Ulmer Ieee Access 8, 58194-58205, 2020 | 230 | 2020 |
| Ensemble methods as a defense to adversarial perturbations against deep neural networks T Strauss, M Hanselmann, A Junginger, H Ulmer arXiv preprint arXiv:1709.03423, 2017 | 180 | 2017 |
| Learning implicit surface light fields M Oechsle, M Niemeyer, C Reiser, L Mescheder, T Strauss, A Geiger 2020 International Conference on 3D Vision (3DV), 452-462, 2020 | 44 | 2020 |
| Comparison of statistical inversion with iteratively regularized Gauss Newton method for image reconstruction in electrical impedance tomography S Ahmad, T Strauss, S Kupis, T Khan Applied Mathematics and Computation 358, 436-448, 2019 | 39 | 2019 |
| Statistical inversion in electrical impedance tomography using mixed total variation and non-convex ℓp regularization prior T Strauss, T Khan Journal of Inverse and Ill-posed Problems 23 (5), 529-542, 2015 | 27 | 2015 |
| Improved Training of Physics-Informed Neural Networks Using Energy-Based Priors: a Study on Electrical Impedance Tomography A Pokkunuru, P Rooshenas, T Strauss, A Abhishek, T Khan The Eleventh International Conference on Learning Representations, 2023 | 12 | 2023 |
| High-Resolution Neural Style Transfer for Test Data Generation for ADAS/HAD Functions A Junginger, M Hanselmann, T Strauss, S Boblest, J Buchner, H Ulmer Automatisiertes Fahren 2020: Von der Fahrerassistenz zum autonomen Fahren 6 …, 2021 | 11* | 2021 |
| Statistical inversion of absolute permeability in single-phase darcy flow T Strauss, X Fan, S Sun, T Khan Procedia Computer Science 51, 1188-1197, 2015 | 10 | 2015 |
| Method and device for recognizing anomalies in a data stream of a communication network A La Marca, M Hanselmann, T Strauss US Patent App. 16/213,649, 2019 | 7 | 2019 |
| Statistical inverse problems in electrical impedance and diffuse optical tomography T Strauss Clemson University, 2015 | 6 | 2015 |
| Comparison of Different Radial Basis Function Networks for the Electrical Impedance Tomography (EIT) Inverse Problem CA Faiyaz, P Shahrear, RA Shamim, T Strauss, T Khan Algorithms 16 (10), 461, 2023 | 3 | 2023 |
| Implicit Solutions of the Electrical Impedance Tomography Inverse Problem in the Continuous Domain with Deep Neural Networks T Strauss, T Khan Entropy 25 (3), 493, 2023 | 3 | 2023 |
| Syncan dataset M Hanselmann, T Strauss, K Dormann, H Ulmer Retrieved August 1, 2021, 2020 | 3 | 2020 |
| Method and apparatus for detecting manipulation of a technical device in a motor vehicle utilizing methods of artificial intelligence A Serout, JS Buchner, M Hanselmann, N Ide, S Nagel, T Branz, T Strauss US Patent App. 17/445,356, 2022 | 2 | 2022 |
| An optimal Bayesian estimator for absorption coefficient in diffuse optical tomography A Abhishek, T Strauss, T Khan SIAM Journal on Imaging Sciences 15 (2), 797-821, 2022 | 2 | 2022 |
| Differentiable Optimization for Orchestration: Resource Offloading for Vehicles in Smart Cities T Strauss, M Oechsle, U Bauknecht IEEE Access, 2024 | 1 | 2024 |
| Computer-implemented method and device for a manipulation detection for exhaust gas treatment systems with the aid of artificial intelligence methods M Hanselmann, JS Buchner, T Strauss, T Branz US Patent App. 17/581,416, 2022 | 1 | 2022 |
| Decision making using a multi-criteria approach in a wholesale electrical power market T Khan, J Reneke, R Grotheer, T Strauss 2015 Clemson University Power Systems Conference (PSC), 1-5, 2015 | 1 | 2015 |
| Solving the Electrical Impedance Tomography Problem with a DeepONet Type Neural Network: Theory and Application A Abhishek, T Strauss arXiv preprint arXiv:2407.17182, 2024 | | 2024 |
Taufiquar KhanUniversity of North Carolina at CharlotteBestätigte E-Mail-Adresse bei uncc.edu
