Pain Level and Pain-Related Behaviour Classification Using GRU-Based Sparsely-Connected RNNs-Reference-Cited by-同舟云学术

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Pain Level and Pain-Related Behaviour Classification Using GRU-Based Sparsely-Connected RNNs

Published:2023-05 Issue:3 Volume:17 Page:677-688
ISSN:1932-4553
Container-title:IEEE Journal of Selected Topics in Signal Processing
language:
Short-container-title:IEEE J. Sel. Top. Signal Process.

Author:

Dehshibi Mohammad Mahdi¹^ORCID,Olugbade Temitayo²^ORCID,Diaz-de-Maria Fernando³^ORCID,Bianchi-Berthouze Nadia²^ORCID,Tajadura-Jiménez Ana⁴^ORCID

Affiliation:

1. i_mBODY Lab, DEI Interactive Systems Group, Department of Computer Science and Engineering, Universidad Carlos III de Madrid, Leganés, Spain

2. UCL Interaction Centre, University College London, London, U.K.

3. Department of Signal Theory and Communications, Universidad Carlos III de Madrid, Leganés, Spain

4. i_mBODY Lab, DEI Interactive Systems Group, Department of Computer Science, Engineering, Universidad Carlos III de Madrid, Leganés, Spain

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Signal Processing

Link

http://xplorestaging.ieee.org/ielx7/4200690/10183711/10083190.pdf?arnumber=10083190

Reference58 articles.

1. A deep multimodal learning approach to perceive basic needs of humans from Instagram profile;dehshibi;IEEE Trans Affect Comput,2021

2. Causal deconvolution by algorithmic generative models

3. Electrical activity of fungi: Spikes detection and complexity analysis

4. Understanding autoencoders with information theoretic concepts

5. Cubic norm and kernel-based bi-directional PCA: toward age-aware facial kinship verification

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