| Convolutional recurrent neural networks for polyphonic sound event detection E Cakir, G Parascandolo, T Heittola, H Huttunen, T Virtanen IEEE/ACM Transactions on Audio, Speech, and Language Processing 25 (6), 1291 …, 2017 | 738 | 2017 |
| Convolutional recurrent neural networks for polyphonic sound event detection E Cakir, G Parascandolo, T Heittola, H Huttunen, T Virtanen IEEE/ACM Transactions on Audio, Speech, and Language Processing 25 (6), 1291 …, 2017 | 738 | 2017 |
| Polyphonic sound event detection using multi label deep neural networks E Cakir, T Heittola, H Huttunen, T Virtanen 2015 international joint conference on neural networks (IJCNN), 1-7, 2015 | 388 | 2015 |
| Stacked convolutional and recurrent neural networks for bird audio detection S Adavanne, K Drossos, E Çakir, T Virtanen 2017 25th European signal processing conference (EUSIPCO), 1729-1733, 2017 | 193 | 2017 |
| Convolutional recurrent neural networks for rare sound event detection E Cakır, T Virtanen Deep Neural Networks for Sound Event Detection 12, 2019 | 75 | 2019 |
| Robust direction estimation with convolutional neural networks based steered response power P Pertilä, E Cakir 2017 IEEE International Conference on Acoustics, Speech and Signal …, 2017 | 74 | 2017 |
| Multi-label vs. combined single-label sound event detection with deep neural networks E Cakir, T Heittola, H Huttunen, T Virtanen 2015 23rd European signal processing conference (EUSIPCO), 2551-2555, 2015 | 66 | 2015 |
| Unsupervised adversarial domain adaptation for acoustic scene classification S Gharib, K Drossos, E Cakir, D Serdyuk, T Virtanen arXiv preprint arXiv:1808.05777, 2018 | 63 | 2018 |
| End-to-end polyphonic sound event detection using convolutional recurrent neural networks with learned time-frequency representation input E Çakir, T Virtanen 2018 International Joint Conference on Neural Networks (IJCNN), 1-7, 2018 | 51 | 2018 |
| Filterbank learning for deep neural network based polyphonic sound event detection E Cakir, EC Ozan, T Virtanen 2016 International Joint Conference on Neural Networks (IJCNN), 3399-3406, 2016 | 47 | 2016 |
| The machine learning approach for analysis of sound scenes and events T Heittola, E Çakır, T Virtanen Computational analysis of sound scenes and events, 13-40, 2018 | 46 | 2018 |
| Domestic audio tagging with convolutional neural networks E Cakır, T Heittola, T Virtanen IEEE AASP challenge on detection and classification of acoustic scenes and …, 2016 | 30 | 2016 |
| Multi-task regularization based on infrequent classes for audio captioning E Çakır, K Drossos, T Virtanen arXiv preprint arXiv:2007.04660, 2020 | 24 | 2020 |
| Automatic recognition of environmental sound events using all-pole group delay features A Diment, E Cakir, T Heittola, T Virtanen 2015 23rd European signal processing conference (EUSIPCO), 729-733, 2015 | 17 | 2015 |
| Acoustic scene classification using convolutional recurrent neural networks H Jallet, E Cakır, T Virtanen the Detection and Classification of Acoustic Scenes and Events (DCASE), 1-5, 2017 | 15 | 2017 |
| Multilabel sound event classification with neural networks E Cakir Tampere University of Technology, Master of Science Thesis, 2014 | 13 | 2014 |
| Deep Neural Networks for Sound Event Detection. E Cakir University of Tampere, Finland, 2019 | 12 | 2019 |
| Musical instrument synthesis and morphing in multidimensional latent space using variational, convolutional recurrent autoencoders E Çakir, T Virtanen Audio Engineering Society Convention 145, 2018 | 6 | 2018 |
| Mobile microphone array speech detection and localization in diverse everyday environments P Pertilä, E Cakir, A Hakala, E Fagerlund, T Virtanen, A Politis, A Eronen 2021 29th European Signal Processing Conference (EUSIPCO), 406-410, 2021 | 5 | 2021 |
| 2017 Index IEEE/ACM Transactions on Audio, Speech, and Language Processing Vol. 25 J Abeber, J Abel, J Abeser, TD Abhayapala, V Abrol, MO Ahmad, ... IEEE/ACM Transactions on Audio, Speech, and Language Processing 25 (12), 2463, 2017 | | 2017 |
Tuomas VirtanenTampere UniversityΗ διεύθυνση ηλεκτρονικού ταχυδρομείου έχει επαληθευτεί στον τομέα tuni.fi
