Methods › Audio › Audio Model Blocks › AUCO ResNet
Auditory Cortex ResNet
AUCO ResNet
Introduced by Vincenzo Dentamaro et al. in AUCO ResNet: an end-to-end network for Covid-19 pre-screening from cough and breath
archive 2025-07-28 Description, source and code snippet are the archive's method entry.
The Auditory Cortex ResNet, briefly AUCO ResNet, is proposed and tested. It is a deep neural network architecture especially designed for audio classification trained end-to-end. It is inspired by the architectural organization of rat's auditory cortex, containing also innovations 2 and 3. The network outperforms the state-of-the-art accuracies on a reference audio benchmark dataset without any kind of preprocessing, imbalanced data handling and, most importantly, any kind of data augmentation.
Papers archive 2025-07-28
1 shown of 1, newest first. Repository counts are the archive's code-links table. A Syntology line states what Syntology ran from that paper's harvested code; it is per sample and not a correctness claim.
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AUCO ResNet: an end-to-end network for Covid-19 pre-screening from cough and breath 15 Mar 2022 · 1 repository
Tasks archive 2025-07-28
8 tasks the archive attaches to papers tagged with this method, by distinct papers. A task without a page in the catalog is plain text.
| Task | Papers |
|---|---|
| 8k | 1 |
| Audio Classification | 1 |
| COVID-19 Diagnosis | 1 |
| Data Augmentation | 1 |
| Dimensionality Reduction | 1 |
| Environmental Sound Classification | 1 |
| Sound Classification | 1 |
| feature selection | 1 |
Usage over time archive 2025-07-28
Components: the archive holds no method-to-method composition, so PwC's Components table cannot be rebuilt; the Papers list carries no Results column for the same reason (the archive does not join its leaderboard rows to method tags).
Categories archive 2025-07-28
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