| Efficient large-scale audio tagging via transformer-to-cnn knowledge distillation F Schmid, K Koutini, G Widmer ICASSP 2023-2023 IEEE International Conference on Acoustics, Speech and …, 2023 | 60 | 2023 |
| CPJKU submission to dcase22: Distilling knowledge for lowcomplexity convolutional neural networks from a patchout audio transformer F Schmid, S Masoudian, K Koutini, G Widmer Tech. Rep., Detection and Classification of Acoustic Scenes and Events …, 2022 | 31 | 2022 |
| Knowledge Distillation from Transformers for Low-Complexity Acoustic Scene Classification. F Schmid, S Masoudian, K Koutini, G Widmer DCASE, 2022 | 20 | 2022 |
| Device-robust acoustic scene classification via impulse response augmentation T Morocutti, F Schmid, K Koutini, G Widmer 2023 31st European Signal Processing Conference (EUSIPCO), 176-180, 2023 | 18 | 2023 |
| CP-JKU submission to dcase23: Efficient acoustic scene classification with cp-mobile F Schmid, T Morocutti, S Masoudian, K Koutini, G Widmer DCASE2023 Challenge, Tech. Rep, 2023 | 18 | 2023 |
| Distilling the knowledge of transformers and CNNs with CP-mobile F Schmid, T Morocutti, S Masoudian, K Koutini, G Widmer Proceedings of the Detection and Classification of Acoustic Scenes and …, 2023 | 13 | 2023 |
| Data-Efficient Low-Complexity Acoustic Scene Classification in the DCASE 2024 Challenge F Schmid, P Primus, T Heittola, A Mesaros, I Martín-Morató, K Koutini, ... arXiv preprint arXiv:2405.10018, 2024 | 12 | 2024 |
| Learning general audio representations with large-scale training of patchout audio transformers K Koutini, S Masoudian, F Schmid, H Eghbal-zadeh, J Schlüter, G Widmer HEAR: Holistic Evaluation of Audio Representations, 65-89, 2022 | 6 | 2022 |
| Low-complexity audio embedding extractors F Schmid, K Koutini, G Widmer 2023 31st European Signal Processing Conference (EUSIPCO), 451-455, 2023 | 5 | 2023 |
| Dynamic Convolutional Neural Networks as Efficient Pre-trained Audio Models F Schmid, K Koutini, G Widmer IEEE/ACM Transactions on Audio, Speech, and Language Processing, 2024 | 3 | 2024 |
| Improving Audio Spectrogram Transformers for Sound Event Detection Through Multi-Stage Training F Schmid, P Primus, T Morocutti, J Greif, G Widmer arXiv preprint arXiv:2408.00791, 2024 | 2 | 2024 |
| Simulation-assisted Training of Neural Networks for Condition Monitoring of Electrical Drives: Approach and Proof of Concept E Marth, P Zorn, F Schmid, S Masoudian, K Koutini, W Amrhein IKMT 2022; 13. GMM/ETG-Symposium, 1-7, 2022 | 2 | 2022 |
| Multi-Iteration Multi-Stage Fine-Tuning of Transformers for Sound Event Detection with Heterogeneous Datasets F Schmid, P Primus, T Morocutti, J Greif, G Widmer arXiv preprint arXiv:2407.12997, 2024 | 1 | 2024 |
| Simulation-assisted Training of Neural Networks for Condition Monitoring of Electrical Drives: Enhanced Domain Adaptation Methods F Schmid, S Masoudian, E Marth, P Zorn, K Koutini, G Widmer IKMT 2022; 13. GMM/ETG-Symposium, 1-7, 2022 | 1 | 2022 |
| Effective Pre-Training of Audio Transformers for Sound Event Detection F Schmid, T Morocutti, F Foscarin, J Schlüter, P Primus, G Widmer arXiv preprint arXiv:2409.09546, 2024 | | 2024 |
| Estimated Audio-Caption Correspondences Improve Language-Based Audio Retrieval P Primus, F Schmid, G Widmer arXiv preprint arXiv:2408.11641, 2024 | | 2024 |
| Improving Query-by-Vocal Imitation with Contrastive Learning and Audio Pretraining J Greif, F Schmid, P Primus, G Widmer arXiv preprint arXiv:2408.11638, 2024 | | 2024 |
| Using domain adaptation to counter distribution shift between training and application domain/submitted by Florian Schmid, Bsc. F Schmid | | 2022 |
| CREATING A GOOD TEACHER FOR KNOWLEDGE DISTILLATION IN ACOUSTIC SCENE CLASSIFICATION T Morocutti, F Schmid, K Koutini, G Widmer | | |
