| Predicting time-to-failure of plasma etching equipment using machine learning A Jalali, C Heistracher, A Schindler, B Haslhofer, T Nemeth, R Glawar, ... 2019 IEEE International Conference on Prognostics and Health Management …, 2019 | 26 | 2019 |
| A conceptual model to enable prescriptive maintenance for etching equipment in semiconductor manufacturing F Biebl, R Glawar, A Jalali, F Ansari, B Haslhofer, P de Boer, W Sihn Procedia CIRP 88, 64-69, 2020 | 21 | 2020 |
| A Low-Compexity Deep Learning Framework For Acoustic Scene Classification L Pham, H Tang, A Jalali, A Schindler, R King arXiv preprint arXiv:2106.06838, 2021 | 5 | 2021 |
| Machine Learning Interpretability Techniques for Outage Prediction: A Comparative Study A Jalali, A Schindler, B Haslhofer, A Rauber PHM Society European Conference 5 (1), 10-10, 2020 | 4 | 2020 |
| Multi-modal video forensic platform for investigating post-terrorist attack scenarios A Schindler, A Lindley, A Jalali, M Boyer, S Gordea, R King Proceedings of the 11th ACM Multimedia Systems Conference, 365-368, 2020 | 4 | 2020 |
| DCASE CHALLENGE 2020: UNSUPERVISED ANOMALOUS SOUND DETECTION OF MACHINERY WITH DEEP AUTOENCODERS A Jalali, A Schindler, B Haslhofer | 4* | |
| Understandable deep neural networks for predictive maintenance in the manufacturing industry AN Jalali, A Schindler, B Haslhofer ERCIM NEWS, 33-34, 2019 | 2 | 2019 |
| Comparison of PSG signals and respiratory movement signal via 3D camera in detecting sleep respiratory events by LSTM models C Coronel, C Wiesmeyr, H Garn, B Kohn, A Naghibzadeh-Jalali, ... 2020 Asia-Pacific Signal and Information Processing Association Annual …, 2020 | 1 | 2020 |
| DCASE CHALLENGE 2021: UNSUPERVISED ANOMALOUS SOUND DETECTION OF MACHINERY WITH LENET ARCHITECTURE L Pham, A Jalali, O Dinica, A Schindler | 1 | |
