| A convolutional neural-network framework for modelling auditory sensory cells and synapses F Drakopoulos, D Baby, S Verhulst Communications Biology 4 (1), 827, 2021 | 27 | 2021 |
| Real-time audio processing on a Raspberry Pi using deep neural networks F Drakopoulos, D Baby, S Verhulst 23rd International Congress on Acoustics (ICA 2019), 2827-2834, 2019 | 14 | 2019 |
| A neural-network framework for the design of individualised hearing-loss compensation F Drakopoulos, S Verhulst IEEE/ACM Transactions on Audio, Speech, and Language Processing 31, 2395-2409, 2023 | 11 | 2023 |
| A differentiable optimisation framework for the design of individualised DNN-based hearing-aid strategies F Drakopoulos, S Verhulst ICASSP 2022-2022 IEEE International Conference on Acoustics, Speech and …, 2022 | 11 | 2022 |
| Model-based hearing-enhancement strategies for cochlear synaptopathy pathologies F Drakopoulos, V Vasilkov, AO Vecchi, T Wartenberg, S Verhulst Hearing Research 424, 108569, 2022 | 9 | 2022 |
| A DNN-based hearing-aid strategy for real-time processing: One size fits all F Drakopoulos, A Van Den Broucke, S Verhulst ICASSP 2023-2023 IEEE International Conference on Acoustics, Speech and …, 2023 | 4 | 2023 |
| Neural network model for cochlear mechanics and processing S Verhulst, D Baby, F Drakopoulos, A Van Den Broucke US Patent 11,800,301, 2023 | 3 | 2023 |
| Large-scale electrophysiology and deep learning reveal distorted neural signal dynamics after hearing loss S Sabesan, A Fragner, C Bench, F Drakopoulos, NA Lesica Elife 12, e85108, 2023 | 2 | 2023 |
| Otoacoustic emissions in a deep-neural-network model of cochlear mechanics A Van Den Broucke, F Drakopoulos, D Baby, S Verhulst The 14th International Mechanics of Hearing Workshop (MoH 2022) 3062, 2024 | 1 | 2024 |
| Otoacoustic emissions in a deep-neural-network model of cochlear mechanics AVD Broucke, F Drakopoulos, D Baby, S Verhulst AIP Conference Proceedings 3062 (1), 2024 | | 2024 |
| Modeling neural coding in the auditory brain with high resolution and accuracy F Drakopoulos, S Sabesan, Y Xia, A Fragner, NA Lesica bioRxiv, 2024.06. 17.599294, 2024 | | 2024 |
| Closed-loop method to individualize neural-network-based audio signal processing S Verhulst, F Drakopoulos, A Van Den Broucke, S Keshishzadeh US Patent App. 17/802,983, 2023 | | 2023 |
| Machine-learning-based audio algorithms for hearing loss compensation M Wouters, F Drakopoulos, S Verhulst Forum Acusticum 2023, 2023 | | 2023 |
| Machine-learning-based audio algorithms for cochlear synaptopathy compensation: which speech features are enhanced? M Wouters, F Drakopoulos, S Verhulst 24th International Congress on Acoustics (ICA 2022), 2022 | | 2022 |
| Novel compensation strategies for hearing-impaired auditory signal processing F Drakopoulos Ghent University, 2022 | | 2022 |
| Biophysically realistic neural-network models of auditory neurons and synapses for neuroscience and machine-hearing applications S Verhulst, F Drakopoulos, A Van den Broucke, D Baby 30th Annual Computational Neuroscience Meeting: CNS* 2021 49 (Suppl. 1), S30-S31, 2021 | | 2021 |
| Applying Biophysical Auditory Periphery Models for Real-time Applications and Studies of Hearing Impairment A van Den Broucke, F Drakopoulos, D Baby, S Verhulst Forum Acusticum, 3005-3006, 2020 | | 2020 |
