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Label-less Learning for Emotion Cognition
7 references·1 citing·39 second hop
Label-less Learning for Emotion Cognition (2019)Label-less Learning for Emotion CognitionAudio-visual emotion fusion (AVEF): A deep efficient weighted approach (2018)Audio-visual emotion fusion (…Speech Emotion Recognition Using Deep Convolutional Neural Network and Discriminant Temporal Pyramid Matching (2017)Speech Emotion Recognition Us…Learning Affective Features With a Hybrid Deep Model for Audio–Visual Emotion Recognition (2017)Learning Affective Features W…End-to-End Multimodal Emotion Recognition Using Deep Neural Networks (2017)End-to-End Multimodal Emotion…AIWAC: affective interaction through wearable computing and cloud technology (2015)AIWAC: affective interaction …Multimodal Emotion Recognition in Response to Videos (2011)Multimodal Emotion Recognitio…The eNTERFACE’05 Audio-Visual Emotion Database (2006)The eNTERFACE’05 Audio-Visual…Emotion Recognition for Cognitive Edge Computing Using Deep Learning (2021)Emotion Recognition for Cogni…Big Data: A Survey (2014)Audio-Visual Emotion Recognition Using Big Data Towards 5G (2016)AVEC 2016 - Depression, Mood, and Emotion Recognition Workshop and Challenge (2016)Emotion Communication System (2016)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)The Cognitive Structure of Emotions (1988)A Review and Meta-Analysis of Multimodal Affect Detection Systems (2015)Analysis of EEG Signals and Facial Expressions for Continuous Emotion Detection (2015)Human Emotion Recognition: Review of Sensors and Methods (2020)Facial Action Coding System (1978)Comprehensive database for facial expression analysis (2002)Emotion recognition using deep learning approach from audio–visual emotional big data (2018)A systematic review on affective computing: emotion models, databases, and recent advances (2022)Emotion recognition and artificial intelligence: A systematic review (2014–2023) and research recommendations (2023)A Concordance Correlation Coefficient to Evaluate Reproducibility (1989)Vocal communication of emotion: A review of research paradigms (2003)The Geneva Minimalistic Acoustic Parameter Set (GeMAPS) for Voice Research and Affective Computing (2015)Speech Emotion Recognition Using Deep Learning Techniques: A Review (2019)Speech emotion recognition: Emotional models, databases, features, preprocessing methods, supporting modalities, and classifiers (2019)Analysis of emotion recognition using facial expressions, speech and multimodal information (2004)A Survey of Affect Recognition Methods: Audio, Visual, and Spontaneous Expressions (2008)Survey on speech emotion recognition: Features, classification schemes, and databases (2010)Deep Learning for Human Affect Recognition: Insights and New Developments (2019)MFCC-based Recurrent Neural Network for automatic clinical depression recognition and assessment from speech (2021)Deep learning-based multimodal emotion recognition from audio, visual, and text modalities: A systematic review of recent advancements and future prospects (2023)Emotion recognition in human-computer interaction (2001)A database of German emotional speech (2005)A CNN-Assisted Enhanced Audio Signal Processing for Speech Emotion Recognition (2019)Clustering-Based Speech Emotion Recognition by Incorporating Learned Features and Deep BiLSTM (2020)Deep Learning Techniques for Speech Emotion Recognition, from Databases to Models (2021)Constants across cultures in the face and emotion. (1971)The Extended Cohn-Kanade Dataset (CK+): A complete dataset for action unit and emotion-specified expression (2010)Going deeper in facial expression recognition using deep neural networks (2016)A Survey on Physiological Signal-Based Emotion Recognition (2022)A systematic review on automated human emotion recognition using electroencephalogram signals and artificial intelligence (2023)An Active Learning Paradigm for Online Audio-Visual Emotion Recognition (2019)Spontaneous Speech Emotion Recognition Using Multiscale Deep Convolutional LSTM (2019)A review of multimodal emotion recognition from datasets, preprocessing, features, and fusion methods (2023)
this work references cited by second hop

References

  • 2017End-to-End Multimodal Emotion Recognition Using Deep Neural Networks749 cited
  • 2011Multimodal Emotion Recognition in Response to Videos723 cited
  • 2006The eNTERFACE’05 Audio-Visual Emotion Database615 cited
  • 2017Speech Emotion Recognition Using Deep Convolutional Neural Network and Discriminant Temporal Pyramid Matching443 cited
  • 2017Learning Affective Features With a Hybrid Deep Model for Audio–Visual Emotion Recognition346 cited
  • 2015AIWAC: affective interaction through wearable computing and cloud technology168 cited
  • 2018Audio-visual emotion fusion (AVEF): A deep efficient weighted approach155 cited

Cited by

  • 2021Emotion Recognition for Cognitive Edge Computing Using Deep Learning107 cited

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