| Pytorch Lightning. 2019 W Falcon, J Borovec, J Schock, A Wälchli, A Mocholi, A Nitta, T Chaton, ... URL https://github. com/PyTorchLightning/pytorch-lightning, 2019 | 897* | 2019 |
| Torchmetrics-measuring reproducibility in pytorch NS Detlefsen, J Borovec, J Schock, AH Jha, T Koker, L Di Liello, D Stancl, ... Journal of Open Source Software 7 (70), 4101, 2022 | 64* | 2022 |
| A thermal infrared face database with facial landmarks and emotion labels M Kopaczka, R Kolk, J Schock, F Burkhard, D Merhof IEEE Transactions on Instrumentation and Measurement 68 (5), 1389-1401, 2018 | 61 | 2018 |
| batchgenerators—a python framework for data augmentation F Isensee, P Jäger, J Wasserthal, D Zimmerer, J Petersen, S Kohl, ... Version 0.19 6, 2020 | 41 | 2020 |
| Automated analysis of alignment in long-leg radiographs by using a fully automated support system based on artificial intelligence J Schock, D Truhn, DB Abrar, D Merhof, S Conrad, M Post, F Mittelstrass, ... Radiology: Artificial Intelligence 3 (2), e200198, 2020 | 29 | 2020 |
| A modular system for detection, tracking and analysis of human faces in thermal infrared recordings M Kopaczka, L Breuer, J Schock, D Merhof Sensors 19 (19), 4135, 2019 | 24 | 2019 |
| A combined modular system for face detection, head pose estimation, face tracking and emotion recognition in thermal infrared images M Kopaczka, J Schock, J Nestler, K Kielholz, D Merhof 2018 IEEE International Conference on Imaging Systems and Techniques (IST), 1-6, 2018 | 23 | 2018 |
| PyTorch lightning. GitHub (March 2019) WA Falcon | 22* | |
| Super-realtime facial landmark detection and shape fitting by deep regression of shape model parameters M Kopaczka, J Schock, D Merhof arXiv preprint arXiv:1902.03459, 2019 | 12 | 2019 |
| A serial multiparametric quantitative magnetic resonance imaging study to assess proteoglycan depletion of human articular cartilage and its effects on functionality T Hafner, J Schock, M Post, DB Abrar, P Sewerin, K Linka, M Knobe, ... Scientific reports 10 (1), 15106, 2020 | 11 | 2020 |
| Deep learning-based post-processing of real-time MRI to assess and quantify dynamic wrist movement in health and disease KL Radke, LM Wollschläger, S Nebelung, DB Abrar, C Schleich, ... Diagnostics 11 (6), 1077, 2021 | 10 | 2021 |
| An MRI-compatible varus–valgus loading device for whole-knee joint functionality assessment based on compartmental compression: A proof-of-concept study O Said, J Schock, N Krämer, J Thüring, L Hitpass, P Schad, C Kuhl, ... Magnetic Resonance Materials in Physics, Biology and Medicine 33, 839-854, 2020 | 9 | 2020 |
| A method for semantic knee bone and cartilage segmentation with deep 3D shape fitting using data from the osteoarthritis initiative J Schock, M Kopaczka, B Agthe, J Huang, P Kruse, D Truhn, S Conrad, ... Shape in Medical Imaging: International Workshop, ShapeMI 2020, Held in …, 2020 | 9 | 2020 |
| Adaptive preprocessing for generalization in cardiac MR image segmentation F Khader, J Schock, D Truhn, F Morsbach, C Haarburger Statistical Atlases and Computational Models of the Heart. M&Ms and EMIDEC …, 2021 | 8 | 2021 |
| Magnetic resonance imaging of human knee joint functionality under variable compressive in-situ loading and axis alignment P Schad, M Wollenweber, J Thüring, J Schock, J Eschweiler, G Palm, ... journal of the mechanical behavior of biomedical materials 110, 103890, 2020 | 8 | 2020 |
| Assessment of laboratory mouse activity in video recordings using deep learning methods M Kopaczka, D Tillmann, L Ernst, J Schock, R Tolba, D Merhof 2019 41st Annual International Conference of the IEEE Engineering in …, 2019 | 8 | 2019 |
| Fast, Accurate, and Robust T2 Mapping of Articular Cartilage by Neural Networks G Müller-Franzes, T Nolte, M Ciba, J Schock, F Khader, A Prescher, ... Diagnostics 12 (3), 688, 2022 | 7 | 2022 |
| No pressure, no diamonds?-Static vs. dynamic compressive in-situ loading to evaluate human articular cartilage functionality by functional MRI D Truhn, KT Zwingenberger, J Schock, DB Abrar, KL Radke, M Post, ... Journal of the mechanical behavior of biomedical materials 120, 104558, 2021 | 6 | 2021 |
| Radiomic feature stability analysis based on probabilistic segmentations C Haarburger, J Schock, D Truhn, P Weitz, G Mueller-Franzes, ... 2020 IEEE 17th International Symposium on Biomedical Imaging (ISBI), 1188-1192, 2020 | 6 | 2020 |
| Using machine learning to study the kinematics of cold gas in galaxies JM Dawson, TA Davis, EL Gomez, J Schock, N Zabel, TG Williams Monthly Notices of the Royal Astronomical Society 491 (2), 2506-2519, 2020 | 6 | 2020 |
William A FalconPhD Student, New York UniversityVerified email at columbia.edu
