| A survey of uncertainty in deep neural networks J Gawlikowski, CRN Tassi, M Ali, J Lee, M Humt, J Feng, A Kruspe, ... Artificial Intelligence Review 56 (Suppl 1), 1513-1589, 2023 | 1352 | 2023 |
| Cross-language sentiment analysis of European Twitter messages during the COVID-19 pandemic A Kruspe, M Haeberle, XX Zhu Workshop on NLP for COVID-19, Annual Meetings of the Association for …, 2020 | 104 | 2020 |
| An advanced dirichlet prior network for out-of-distribution detection in remote sensing J Gawlikowski, S Saha, A Kruspe, XX Zhu IEEE Transactions on Geoscience and Remote Sensing 60, 1-19, 2022 | 55 | 2022 |
| An Introduction to Signal Processing for Singing-Voice Analysis: High Notes in the Effort to Automate the Understanding of Vocals in Music EJ Humphrey, S Reddy, P Seetharaman, A Kumar, RM Bittner, ... IEEE Signal Processing Magazine 36 (1), 82-94, 2018 | 53 | 2018 |
| Bootstrapping a system for phoneme recognition and keyword spotting in unaccompanied singing AM Kruspe Proceedings of 17th International Society for Music Information Retrieval …, 2016 | 46 | 2016 |
| Detection of actionable tweets in crisis events A Kruspe, J Kersten, F Klan Natural Hazards and Earth System Sciences 21 (6), 1825-1845, 2021 | 44 | 2021 |
| Changes in Twitter geolocations: Insights and suggestions for future usage A Kruspe, M Häberle, EJ Hoffmann, S Rode-Hasinger, K Abdulahhad, ... arXiv preprint arXiv:2108.12251, 2021 | 39 | 2021 |
| Robust filtering of crisis-related tweets J Kersten, A Kruspe, M Wiegmann, F Klan Information Systems for Crisis Response and Management (ISCRAM), 2019 | 39 | 2019 |
| Deutsche Normungsroadmap Künstliche Intelligenz R Adler, S Kolomiichuk, D Hecker, P Lämmel, J Ma, A Marko, M Mock, ... DIN, 2020 | 33 | 2020 |
| A Survey of Uncertainty in Deep Neural Networks, arXiv J Gawlikowski, CRN Tassi, M Ali, J Lee, M Humt, J Feng, A Kruspe, ... arXiv preprint arXiv:2107.03342, 2021 | 30 | 2021 |
| Geoinformation Harvesting From Social Media Data: A community remote sensing approach XX Zhu, Y Wang, M Kochupillai, M Werner, M Häberle, EJ Hoffmann, ... IEEE Geoscience and Remote Sensing Magazine 10 (4), 150-180, 2022 | 29 | 2022 |
| Training phoneme models for singing with “songified” speech data AM Kruspe Proceedings of the 16th International Society for Music Information …, 2015 | 26* | 2015 |
| A survey of uncertainty in deep neural networks. arXiv 2021 J Gawlikowski, CRN Tassi, M Ali, J Lee, M Humt, J Feng, A Kruspe, ... arXiv preprint arXiv:2107.03342, 0 | 26 | |
| Detection of informative tweets in crisis events A Kruspe, J Kersten, F Klan Natural Hazards and Earth System Sciences (NHESS), 2021 | 23 | 2021 |
| Detecting event-related tweets by example using few-shot models A Kruspe, J Kersten, F Klan Information Systems for Crisis Response and Management (ISCRAM), 2019 | 21 | 2019 |
| Automatic classification of musical pieces into global cultural areas A Kruspe, H Lukashevich, J Abeßer, H Großmann, C Dittmar Audio Engineering Society Conference: 42nd International Conference …, 2011 | 21 | 2011 |
| Analysis of Railway Track Irregularities with Convolutional Autoencoders and Clustering Algorithms J Niebling, B Baasch, A Kruspe European Dependable Computing Conference, 78-89, 2020 | 20 | 2020 |
| Keyword spotting in a-capella singing AM Kruspe Proceedings of the 15th International Society for Music Information …, 2014 | 20 | 2014 |
| Impact of Training Set Size on the Ability of Deep Neural Networks to Deal with Omission Noise J Gütter, A Kruspe, XX Zhu, J Niebling Frontiers in Remote Sensing, 61, 2022 | 18 | 2022 |
| One-Way Prototypical Networks A Kruspe arXiv preprint arXiv:1906.00820, 2019 | 18 | 2019 |
Xiao Xiang ZhuTechnical University of MunichE-mail megerősítve itt: tum.de