OFFICIAL REPOSITORY

AUCO ResNet: an end-to-end network for Covid-19 pre-screening from cough and breath

AUCO ResNet: an end-to-end network for Covid-19 pre-screening from cough and breath

Dentamaro, V., Giglio, P., Impedovo, D., Moretti, L., & Pirlo, G. (2022). AUCO ResNet: an end-to-end network for Covid-19 pre-screening from cough and breath. Pattern Recognition, 108656. doi:10.1016/j.patcog.2022.108656

• 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.

• A trainable Mel-like spectrogram layer able to finetune the
  Mel-like-Spectrogram for capturing relevant time frequency
  information.

• A novel sinusoidal learnable attention mechanism which can be
  considered as a technique to weight local and global feature
  descriptors focusing on high frequency details.

• State of the art cross-dataset testing and related accuracies.