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Emotion Recognition of Students Based on Facial Expressions in Online Education Based on the Perspective of Computer Simulation
12 references·2 citing·46 second hop
Emotion Recognition of Students Based on Facial Expressions in Online Education Based on the Perspective of Computer Simulation (2020)Emotion Recognition of Students Based on …Automatic recognition of student emotions from facial expressions during a lecture (2020)Automatic recognition of stud…Attention mechanism-based CNN for facial expression recognition (2020)Attention mechanism-based CNN…Using CNN for facial expression recognition: a study of the effects of kernel size and number of filters on accuracy (2019)Using CNN for facial expressi…Three convolutional neural network models for facial expression recognition in the wild (2019)Three convolutional neural ne…Peak-Piloted Deep Network for Facial Expression Recognition (2016)Peak-Piloted Deep Network for…Automatic Analysis of Facial Affect: A Survey of Registration, Representation, and Recognition (2014)Automatic Analysis of Facial …Collecting Large, Richly Annotated Facial-Expression Databases from Movies (2012)Collecting Large, Richly Anno…Categorical and dimensional affect analysis in continuous input: Current trends and future directions (2012)Categorical and dimensional a…A Survey of Affect Recognition Methods: Audio, Visual, and Spontaneous Expressions (2008)A Survey of Affect Recognitio…The universality of a contempt expression: A replication (1988)The universality of a contemp…Measuring facial movement (1976)Measuring facial movementConstants across cultures in the face and emotion. (1971)Constants across cultures in …Exploring contactless techniques in multimodal emotion recognition: insights into diverse applications, challenges, solutions, and prospects (2024)Exploring contactless techniq…Fine-Grained Interpretability for EEG Emotion Recognition: Concat-Aided Grad-CAM and Systematic Brain Functional Network (2023)Fine-Grained Interpretability…The expression of the emotions in man and animals. (1872)Facial Action Coding System (1978)The Extended Cohn-Kanade Dataset (CK+): A complete dataset for action unit and emotion-specified expression (2010)Deep Learning for Emotion Recognition on Small Datasets using Transfer Learning (2015)Survey on Emotional Body Gesture Recognition (2018)A systematic review on affective computing: emotion models, databases, and recent advances (2022)Kinesics and context (1970)Facial signs of emotional experience. 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(2002)Experimental Psychology (1939)EXPERIMENTAL PSYCHOLOGY (1940)American-Japanese Cultural Differences in Judgements of Expression Intensity and Subjective Experience (1999)Idiocentric and allocentric differences in emotional expression, experience, and the coherence between expression and experience (2001)The Relationship Among Expressions, Labels, and Descriptions of Contempt. (2004)A circumplex model of affect. (1980)DEAP: A Database for Emotion Analysis ;Using Physiological Signals (2011)AFEW-VA database for valence and arousal estimation in-the-wild (2017)Deep Learning for Human Affect Recognition: Insights and New Developments (2019)SEWA DB: A Rich Database for Audio-Visual Emotion and Sentiment Research in the Wild (2019)Development and validation of brief measures of positive and negative affect: The PANAS scales. (1988)Development and validation of brief measures of positive and negative affect: The PANAS scales. (1988)Affective Computing (1997)Affect Detection: An Interdisciplinary Review of Models, Methods, and Their Applications (2010)A Multimodal Database for Affect Recognition and Implicit Tagging (2011)Deep Facial Expression Recognition: A Survey (2020)A Decision-Theoretic Generalization of On-Line Learning and an Application to Boosting (1997)Joint Fine-Tuning in Deep Neural Networks for Facial Expression Recognition (2015)Deep Pain: Exploiting Long Short-Term Memory Networks for Facial Expression Classification (2017)Feature Decomposition and Reconstruction Learning for Effective Facial Expression Recognition (2021)Robust Lightweight Facial Expression Recognition Network with Label Distribution Training (2021)Going deeper in facial expression recognition using deep neural networks (2016)Facial Expression Recognition by De-expression Residue Learning (2018)Facial Expression Recognition With Visual Transformers and Attentional Selective Fusion (2021)Distract Your Attention: Multi-Head Cross Attention Network for Facial Expression Recognition (2023)Facial expression recognition with grid-wise attention and visual transformer (2021)A comprehensive survey on deep facial expression recognition: challenges, applications, and future guidelines (2023)Emotion recognition from unimodal to multimodal analysis: A review (2023)
this work references cited by second hop

References

  • 1971Constants across cultures in the face and emotion.5,506 cited
  • 2008A Survey of Affect Recognition Methods: Audio, Visual, and Spontaneous Expressions2,797 cited
  • 1976Measuring facial movement1,230 cited
  • 2014Automatic Analysis of Facial Affect: A Survey of Registration, Representation, and Recognition685 cited
  • 2012Collecting Large, Richly Annotated Facial-Expression Databases from Movies664 cited
  • 2012Categorical and dimensional affect analysis in continuous input: Current trends and future directions360 cited
  • 2020Attention mechanism-based CNN for facial expression recognition348 cited
  • 2016Peak-Piloted Deep Network for Facial Expression Recognition319 cited
  • 2019Using CNN for facial expression recognition: a study of the effects of kernel size and number of filters on accuracy293 cited
  • 1988The universality of a contempt expression: A replication195 cited
  • 2019Three convolutional neural network models for facial expression recognition in the wild186 cited
  • 2020Automatic recognition of student emotions from facial expressions during a lecture154 cited

Cited by

  • 2023Fine-Grained Interpretability for EEG Emotion Recognition: Concat-Aided Grad-CAM and Systematic Brain Functional Network60 cited
  • 2024Exploring contactless techniques in multimodal emotion recognition: insights into diverse applications, challenges, solutions, and prospects

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56 cited