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ORCIDKhaled Koutini
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2020 – today
- 2024
[j3]Hamid Eghbal-zadeh
, Werner Zellinger, Maura Pintor, Kathrin Grosse, Khaled Koutini, Bernhard Alois Moser, Battista Biggio, Gerhard Widmer:
Rethinking data augmentation for adversarial robustness. Inf. Sci. 654: 119838 (2024)- [j2]Florian Schmid, Khaled Koutini, Gerhard Widmer:
Dynamic Convolutional Neural Networks as Efficient Pre-Trained Audio Models. IEEE ACM Trans. Audio Speech Lang. Process. 32: 2227-2241 (2024) - [i19]Florian Schmid, Paul Primus, Toni Heittola, Annamaria Mesaros, Irene Martín-Morató, Khaled Koutini, Gerhard Widmer:
Data-Efficient Low-Complexity Acoustic Scene Classification in the DCASE 2024 Challenge. CoRR abs/2405.10018 (2024) - 2023
- [c14]Tobias Morocutti, Florian Schmid, Khaled Koutini, Gerhard Widmer:
Device-Robust Acoustic Scene Classification via Impulse Response Augmentation. EUSIPCO 2023: 176-180 - [c13]Shahed Masoudian, Khaled Koutini, Markus Schedl, Gerhard Widmer, Navid Rekabsaz:
Domain Information Control at Inference Time for Acoustic Scene Classification. EUSIPCO 2023: 181-185 - [c12]Florian Schmid, Khaled Koutini, Gerhard Widmer:
Low-Complexity Audio Embedding Extractors. EUSIPCO 2023: 451-455 - [c11]Florian Schmid, Khaled Koutini, Gerhard Widmer:
Efficient Large-Scale Audio Tagging Via Transformer-to-CNN Knowledge Distillation. ICASSP 2023: 1-5 - [i18]Florian Schmid, Khaled Koutini, Gerhard Widmer:
Low-Complexity Audio Embedding Extractors. CoRR abs/2303.01879 (2023) - [i17]Tobias Morocutti, Florian Schmid, Khaled Koutini, Gerhard Widmer:
Device-Robust Acoustic Scene Classification via Impulse Response Augmentation. CoRR abs/2305.07499 (2023) - [i16]Shahed Masoudian, Khaled Koutini, Markus Schedl, Gerhard Widmer, Navid Rekabsaz:
Domain Information Control at Inference Time for Acoustic Scene Classification. CoRR abs/2306.08010 (2023) - [i15]Paul Primus, Khaled Koutini, Gerhard Widmer:
Advancing Natural-Language Based Audio Retrieval with PaSST and Large Audio-Caption Data Sets. CoRR abs/2308.04258 (2023) - [i14]Florian Schmid, Khaled Koutini, Gerhard Widmer:
Dynamic Convolutional Neural Networks as Efficient Pre-trained Audio Models. CoRR abs/2310.15648 (2023) - 2022
- [c10]Florian Schmid, Shahed Masoudian, Khaled Koutini, Gerhard Widmer:
Knowledge Distillation from Transformers for Low-Complexity Acoustic Scene Classification. DCASE 2022 - [c9]Khaled Koutini, Jan Schlüter, Hamid Eghbal-zadeh, Gerhard Widmer:
Efficient Training of Audio Transformers with Patchout. INTERSPEECH 2022: 2753-2757 - [i13]Florian Schmid, Khaled Koutini, Gerhard Widmer:
Efficient Large-scale Audio Tagging via Transformer-to-CNN Knowledge Distillation. CoRR abs/2211.04772 (2022) - [i12]Khaled Koutini, Shahed Masoudian, Florian Schmid, Hamid Eghbal-zadeh, Jan Schlüter, Gerhard Widmer:
Learning General Audio Representations with Large-Scale Training of Patchout Audio Transformers. CoRR abs/2211.13956 (2022) - 2021
- [j1]Khaled Koutini, Hamid Eghbal-zadeh, Gerhard Widmer:
Receptive Field Regularization Techniques for Audio Classification and Tagging With Deep Convolutional Neural Networks. IEEE ACM Trans. Audio Speech Lang. Process. 29: 1987-2000 (2021) - [c8]Khaled Koutini, Shahed Masoudian, Florian Schmid, Hamid Eghbal-zadeh, Jan Schlüter, Gerhard Widmer:
Learning General Audio Representations With Large-Scale Training of Patchout Audio Transformers. HEAR@NeurIPS 2021: 65-89 - [i11]Khaled Koutini, Hamid Eghbal-zadeh, Gerhard Widmer:
Receptive Field Regularization Techniques for Audio Classification and Tagging with Deep Convolutional Neural Networks. CoRR abs/2105.12395 (2021) - [i10]Khaled Koutini, Hamid Eghbal-zadeh, Florian Henkel, Jan Schlüter, Gerhard Widmer:
Over-Parameterization and Generalization in Audio Classification. CoRR abs/2107.08933 (2021) - [i9]Khaled Koutini, Jan Schlüter, Hamid Eghbal-zadeh, Gerhard Widmer:
Efficient Training of Audio Transformers with Patchout. CoRR abs/2110.05069 (2021) - 2020
- [c7]Khaled Koutini, Florian Henkel, Hamid Eghbal-Zadeh, Gerhard Widmer:
Low-Complexity Models for Acoustic Scene Classification Based on Receptive Field Regularization and Frequency Damping. DCASE 2020: 86-90 - [i8]Hamid Eghbal-zadeh, Khaled Koutini, Paul Primus, Verena Haunschmid, Michal Lewandowski, Werner Zellinger, Bernhard Alois Moser, Gerhard Widmer:
On Data Augmentation and Adversarial Risk: An Empirical Analysis. CoRR abs/2007.02650 (2020) - [i7]Khaled Koutini, Hamid Eghbal-Zadeh, Verena Haunschmid, Paul Primus, Shreyan Chowdhury, Gerhard Widmer:
Receptive-Field Regularized CNNs for Music Classification and Tagging. CoRR abs/2007.13503 (2020) - [i6]Khaled Koutini, Florian Henkel, Hamid Eghbal-zadeh, Gerhard Widmer:
Low-Complexity Models for Acoustic Scene Classification Based on Receptive Field Regularization and Frequency Damping. CoRR abs/2011.02955 (2020)
2010 – 2019
- 2019
- [c6]Khaled Koutini, Hamid Eghbal-zadeh, Gerhard Widmer:
Receptive-Field-Regularized CNN Variants for Acoustic Scene Classification. DCASE 2019: 124-128 - [c5]Paul Primus, Hamid Eghbal-zadeh, David Eitelsebner, Khaled Koutini, Andreas Arzt, Gerhard Widmer:
Exploiting Parallel Audio Recordings to Enforce Device Invariance in CNN-based Acoustic Scene Classification. DCASE 2019: 204-208 - [c4]Khaled Koutini, Hamid Eghbal-zadeh, Matthias Dorfer, Gerhard Widmer:
The Receptive Field as a Regularizer in Deep Convolutional Neural Networks for Acoustic Scene Classification. EUSIPCO 2019: 1-5 - [c3]Khaled Koutini, Shreyan Chowdhury, Verena Haunschmid, Hamid Eghbal-Zadeh, Gerhard Widmer:
Emotion and Theme Recognition in Music with Frequency-Aware RF-Regularized CNNs. MediaEval 2019 - [i5]Khaled Koutini, Hamid Eghbal-zadeh, Matthias Dorfer, Gerhard Widmer:
The Receptive Field as a Regularizer in Deep Convolutional Neural Networks for Acoustic Scene Classification. CoRR abs/1907.01803 (2019) - [i4]Khaled Koutini, Hamid Eghbal-zadeh, Gerhard Widmer:
Receptive-field-regularized CNN variants for acoustic scene classification. CoRR abs/1909.02859 (2019) - [i3]Paul Primus, Hamid Eghbal-zadeh, David Eitelsebner, Khaled Koutini, Andreas Arzt, Gerhard Widmer:
Exploiting Parallel Audio Recordings to Enforce Device Invariance in CNN-based Acoustic Scene Classification. CoRR abs/1909.02869 (2019) - [i2]Khaled Koutini, Shreyan Chowdhury, Verena Haunschmid, Hamid Eghbal-zadeh, Gerhard Widmer:
Emotion and Theme Recognition in Music with Frequency-Aware RF-Regularized CNNs. CoRR abs/1911.05833 (2019) - 2018
- [c2]Khaled Koutini, Hamid Eghbal-zadeh, Gerhard Widmer:
Iterative knowledge distillation in R-CNNs for weakly-labeled semi-supervised sound event detection. DCASE 2018: 173-177 - [i1]Hamid Eghbal-zadeh, Lukas Fischer, Niko Popitsch, Florian Kromp, Sabine Taschner-Mandl, Khaled Koutini, Teresa Gerber, Eva Bozsaky, Peter F. Ambros, Inge M. Ambros, Gerhard Widmer, Bernhard Alois Moser:
Deep SNP: An End-to-end Deep Neural Network with Attention-based Localization for Break-point Detection in SNP Array Genomic data. CoRR abs/1806.08840 (2018) - 2017
- [c1]Khaled Koutini, Alina Imenina, Matthias Dorfer, Alexander Gruber, Markus Schedl:
MediaEval 2017 AcousticBrainz Genre Task: Multilayer Perceptron Approach. MediaEval 2017
Coauthor Index
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