Deep learning of facial embeddings and facial landmark points for the detection of academic emotions-Reference-Cited by-同舟云学术

Deep learning of facial embeddings and facial landmark points for the detection of academic emotions

Published:2020-07-26 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 5th International Conference on Information and Education Innovations
language:
Short-container-title:

Author:

Leong Fwa Hua¹

Affiliation:

1. Nanyang Polytechnic, School of Information Technology, Singapore, Singapore

Funder

Ministry of Education - Singapore

Publisher

ACM

Reference27 articles.

1. Ran Breuer and Ron Kimmel. 2017. A deep learning perspective on the origin of facial expressions. arXiv preprint arXiv:1705.01842 (2017). Ran Breuer and Ron Kimmel. 2017. A deep learning perspective on the origin of facial expressions. arXiv preprint arXiv:1705.01842 (2017).

2. VGGFace2: A Dataset for Recognising Faces across Pose and Age

3. Learning Spatial and Temporal Cues for Multi-Label Facial Action Unit Detection

4. Matthew Day. 2016. Exploiting facial landmarks for emotion recognition in the wild. arXiv preprint arXiv:1603.09129 (2016). Matthew Day. 2016. Exploiting facial landmarks for emotion recognition in the wild. arXiv preprint arXiv:1603.09129 (2016).

5. Engagement detection in online learning: a review

Cited by 8 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Affect Analysis: A Literature Survey on Student-Specific and General Users’ Affect Analysis;Lecture Notes in Networks and Systems;2024

2. Applications of convolutional neural networks in education: A systematic literature review;Expert Systems with Applications;2023-11

3. Academic Emotion Classification Using FER: A Systematic Review;Human Behavior and Emerging Technologies;2023-05-03

4. Classification of Student Affective States in Online Learning using Neural Networks;2022 17th International Workshop on Semantic and Social Media Adaptation & Personalization (SMAP);2022-11-03

5. Survey on Emotion Sensing Using Mobile Devices;IEEE Transactions on Affective Computing;2022