A practical guide to applying machine learning to infant EEG data

Autor: Bernard Ng, Rebecca K. Reh, Sara Mostafavi

Publikováno v: Developmental Cognitive Neuroscience, Vol 54, Iss , Pp 101096- (2022)

Electroencephalography (EEG) has been widely adopted by the developmental cognitive neuroscience community, but the application of machine learning (ML) in this domain lags behind adult EEG studies. Applying ML to infant data is particularly challeng

Externí odkaz: https://doaj.org/article/80044d141a3040f3ba5aa8b782124183

Fusion of Physiological and Behavioural Signals on SPD Manifolds with Application to Stress and Pain Detection

Autor: Yujin Wu, Mohamed Daoudi, Ali Amad, Laurent Sparrow, Fabien D'Hondt

Publikováno v: International Conference on Systems, Man, and Cybernetics
International Conference on Systems, Man, and Cybernetics, Oct 2022, Prague, Czech Republic

Existing multimodal stress/pain recognition approaches generally extract features from different modalities independently and thus ignore cross-modality correlations. This paper proposes a novel geometric framework for multimodal stress/pain detectio

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a7ee3e0d06d990efce2019685201a74d
http://arxiv.org/abs/2207.08811

Automatic Analysis of Facial Expressions Based on Deep Covariance Trajectories

Autor: Anis Kacem, Naima Otberdout, Mohamed Daoudi, Lahoucine Ballihi, Stefano Berretti

Publikováno v: IEEE Transactions on Neural Networks and Learning Systems
IEEE Transactions on Neural Networks and Learning Systems, IEEE, 2020, 31 (10), pp.3892-3905. ⟨10.1109/TNNLS.2019.2947244⟩
IEEE Transactions on Neural Networks and Learning Systems, 2020, 31 (10), pp.3892-3905. ⟨10.1109/TNNLS.2019.2947244⟩

In this paper, we propose a new approach for facial expression recognition using deep covariance descriptors. The solution is based on the idea of encoding local and global Deep Convolutional Neural Network (DCNN) features extracted from still images

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d8b22c646d7c1ec6bf66d2738e19280e
https://hal.archives-ouvertes.fr/hal-02369410

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