Detecting COVID-19 from breathing and coughing sounds using deep neural networks

to related objects

Location: Deutsche Nationalbibliothek Frankfurt am Main

Extent: Online-Ressource

Language: Englisch

Notes: In: 34th International Symposium on Computer-Based Medical Systems (CBMS 2021), Aveiro, Portugal, 7-9 June 2021, S. 183-188

Event: Veröffentlichung

(where): Augsburg

(who): Universität Augsburg

(when): 2021

Event: Veröffentlichung

(where): New York, NY

(who): IEEE

(when): 2021

Creator: Nessiem, Mina A.
Mohamed, Mostafa M.
Coppock, Harry
Gaskell, Alexander
Schuller, Björn

Contributor: Oliveira, José Luís
Traina, Agma
Soda, Paolo
Arrais, Joel
Kane, Bridget

DOI: 10.1109/cbms52027.2021.00069

URN: urn:nbn:de:bvb:384-opus4-915892

Rights: Der Zugriff auf das Objekt ist unbeschränkt möglich.

Last update: 15.08.2025, 7:36 AM CEST

Data provider

This object is provided by:
Deutsche Nationalbibliothek. If you have any questions about the object, please contact the data provider.

Show original at data provider

Associated

Nessiem, Mina A.
Mohamed, Mostafa M.
Coppock, Harry
Gaskell, Alexander
Schuller, Björn
Oliveira, José Luís
Traina, Agma
Soda, Paolo
Arrais, Joel
Kane, Bridget
Universität Augsburg
IEEE

Time of origin

2021

Other Objects (12)

IEEE Transactions on Affective Computing – on novelty and valence [Editorial]

Editorial: Transactions on Affective Computing - good reasons for joy and excitement

Automatic speaker analysis 2.0: hearing the bigger picture

End-to-end audio classification with small datasets: making it work

Audio watermarking based on empirical mode decomposition and beat detection

Modelling sample informativeness for deep affective computing

Convolutional RNN: an enhanced model for extracting features from sequential data

COVID-19 detection with a novel multi-type deep fusion method using breathing and coughing information

GPU-based training of autoencoders for bird sound data processing

Transformer-based CNNs: mining temporal context information for multi-sound COVID-19 diagnosis

Guest editorial: special section on naturalistic affect resources for system building and evaluation

Tendencies regarding the effect of emotional intensity in inter corpus phoneme-level speech emotion modelling

IEEE Transactions on Affective Computing – on novelty and valence [Editorial]

Editorial: Transactions on Affective Computing - good reasons for joy and excitement

Automatic speaker analysis 2.0: hearing the bigger picture

End-to-end audio classification with small datasets: making it work

Audio watermarking based on empirical mode decomposition and beat detection

Modelling sample informativeness for deep affective computing

Convolutional RNN: an enhanced model for extracting features from sequential data

COVID-19 detection with a novel multi-type deep fusion method using breathing and coughing information

GPU-based training of autoencoders for bird sound data processing

Transformer-based CNNs: mining temporal context information for multi-sound COVID-19 diagnosis

Guest editorial: special section on naturalistic affect resources for system building and evaluation

Tendencies regarding the effect of emotional intensity in inter corpus phoneme-level speech emotion modelling

IEEE Transactions on Affective Computing – on novelty and valence [Editorial]

Editorial: Transactions on Affective Computing - good reasons for joy and excitement

Automatic speaker analysis 2.0: hearing the bigger picture

End-to-end audio classification with small datasets: making it work

Audio watermarking based on empirical mode decomposition and beat detection

Modelling sample informativeness for deep affective computing

Convolutional RNN: an enhanced model for extracting features from sequential data

COVID-19 detection with a novel multi-type deep fusion method using breathing and coughing information

GPU-based training of autoencoders for bird sound data processing

Transformer-based CNNs: mining temporal context information for multi-sound COVID-19 diagnosis

Guest editorial: special section on naturalistic affect resources for system building and evaluation

Tendencies regarding the effect of emotional intensity in inter corpus phoneme-level speech emotion modelling

Cultural heritage institutions wishing to register will find more information here.

Fields marked * need to be filled in.

Username*

Please enter your username

Email*

Please enter your email address

Please do not fill this field

First name

Last name

Password*

Please enter your password

Confirm password*

Please enter the same password

I have read the terms of use and the privacy policy for the collection of personal data and accept them. *

This field is required.

I would like to subscribe to the newsletter of the Deutsche Digitale Bibliothek. See newsletter subscription info.

Account created

Your "My DDB" account has been successfully created. Before you can log in to your account, you must click the confirmation link in the message we just sent to the email address you provided.

Detecting COVID-19 from breathing and coughing sounds using deep neural networks

Object Details

Contributors, Places and Time

Further information

Data provider

Associated

Time of origin

Other Objects (12)

IEEE Transactions on Affective Computing – on novelty and valence [Editorial]

Editorial: Transactions on Affective Computing - good reasons for joy and excitement

Automatic speaker analysis 2.0: hearing the bigger picture

End-to-end audio classification with small datasets: making it work

Audio watermarking based on empirical mode decomposition and beat detection

Modelling sample informativeness for deep affective computing

Convolutional RNN: an enhanced model for extracting features from sequential data

COVID-19 detection with a novel multi-type deep fusion method using breathing and coughing information

GPU-based training of autoencoders for bird sound data processing

Transformer-based CNNs: mining temporal context information for multi-sound COVID-19 diagnosis

Guest editorial: special section on naturalistic affect resources for system building and evaluation

Tendencies regarding the effect of emotional intensity in inter corpus phoneme-level speech emotion modelling

IEEE Transactions on Affective Computing – on novelty and valence [Editorial]

Editorial: Transactions on Affective Computing - good reasons for joy and excitement

Automatic speaker analysis 2.0: hearing the bigger picture

End-to-end audio classification with small datasets: making it work

Audio watermarking based on empirical mode decomposition and beat detection

Modelling sample informativeness for deep affective computing

Convolutional RNN: an enhanced model for extracting features from sequential data

COVID-19 detection with a novel multi-type deep fusion method using breathing and coughing information

GPU-based training of autoencoders for bird sound data processing

Transformer-based CNNs: mining temporal context information for multi-sound COVID-19 diagnosis

Guest editorial: special section on naturalistic affect resources for system building and evaluation

Tendencies regarding the effect of emotional intensity in inter corpus phoneme-level speech emotion modelling

IEEE Transactions on Affective Computing – on novelty and valence [Editorial]

Editorial: Transactions on Affective Computing - good reasons for joy and excitement

Automatic speaker analysis 2.0: hearing the bigger picture

End-to-end audio classification with small datasets: making it work

Audio watermarking based on empirical mode decomposition and beat detection

Modelling sample informativeness for deep affective computing

Convolutional RNN: an enhanced model for extracting features from sequential data

COVID-19 detection with a novel multi-type deep fusion method using breathing and coughing information

GPU-based training of autoencoders for bird sound data processing

Transformer-based CNNs: mining temporal context information for multi-sound COVID-19 diagnosis

Guest editorial: special section on naturalistic affect resources for system building and evaluation

Tendencies regarding the effect of emotional intensity in inter corpus phoneme-level speech emotion modelling

Related objects

Reset password