Improving Facial Expression Recognition Through Data Preparation and Merging-Reference-Cited by-同舟云学术

Improving Facial Expression Recognition Through Data Preparation and Merging

Published:2023 Issue: Volume:11 Page:71339-71360
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Mejia-Escobar Christian¹^ORCID,Cazorla Miguel²^ORCID,Martinez-Martin Ester²^ORCID

Affiliation:

1. FIGEMPA, Central University of Ecuador, Quito, Ecuador

2. Institute for Computer Research, University of Alicante, Alicante, Spain

Funder

Conselleria de Innovaci?n, Universidades, Ciencia y Sociedad Digital, Generalitat Valenciana

Universidad Central del Ecuador

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science,Electrical and Electronic Engineering

Link

http://xplorestaging.ieee.org/ielx7/6287639/10005208/10177163.pdf?arnumber=10177163

Reference61 articles.

1. Cross-dataset emotion recognition from facial expressions through convolutional neural networks

2. LAION-5b: An open large-scale dataset for training next generation image-text models;schuhmann;Proc 36th Conf Neural Inf Process Syst Datasets Benchmarks Track,2022

3. 2D+3D facial expression recognition via discriminative dynamic range enhancement and multi-scale learning;jiao;arXiv 2011 08333,2020

4. A systematic review on affective computing: emotion models, databases, and recent advances

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