Emotion recognition using multi-modal data and machine learning techniques: A tutorial and review
In recent years, the rapid advances in machine learning (ML) and information fusion has
made it possible to endow machines/computers with the ability of emotion understanding …
made it possible to endow machines/computers with the ability of emotion understanding …
A systematic literature review on multimodal machine learning: Applications, challenges, gaps and future directions
Multimodal machine learning (MML) is a tempting multidisciplinary research area where
heterogeneous data from multiple modalities and machine learning (ML) are combined to …
heterogeneous data from multiple modalities and machine learning (ML) are combined to …
Deep learning for human affect recognition: Insights and new developments
Automatic human affect recognition is a key step towards more natural human-computer
interaction. Recent trends include recognition in the wild using a fusion of audiovisual and …
interaction. Recent trends include recognition in the wild using a fusion of audiovisual and …
End-to-end multimodal emotion recognition using deep neural networks
Automatic affect recognition is a challenging task due to the various modalities emotions can
be expressed with. Applications can be found in many domains including multimedia …
be expressed with. Applications can be found in many domains including multimedia …
AFEW-VA database for valence and arousal estimation in-the-wild
Continuous dimensional models of human affect, such as those based on valence and
arousal, have been shown to be more accurate in describing a broad range of spontaneous …
arousal, have been shown to be more accurate in describing a broad range of spontaneous …
Multimodal multi-task learning for dimensional and continuous emotion recognition
Automatic emotion recognition is a challenging task which can make great impact on
improving natural human computer interactions. In this paper, we present our effort for the …
improving natural human computer interactions. In this paper, we present our effort for the …
Transformer encoder with multi-modal multi-head attention for continuous affect recognition
Continuous affect recognition is becoming an increasingly attractive research topic in
affective computing. Previous works mainly focused on modelling the temporal dependency …
affective computing. Previous works mainly focused on modelling the temporal dependency …
[HTML][HTML] A review of recent approaches for emotion classification using electrocardiography and electrodermography signals
AF Bulagang, NG Weng, J Mountstephens… - Informatics in Medicine …, 2020 - Elsevier
This paper reviews emotion classification investigations, focusing on the use of the
Electrocardiogram (ECG) and Electrodermography (EDG)/Galvanic Skin Response (GSR) …
Electrocardiogram (ECG) and Electrodermography (EDG)/Galvanic Skin Response (GSR) …
A review of recurrent neural network-based methods in computational physiology
Artificial intelligence and machine learning techniques have progressed dramatically and
become powerful tools required to solve complicated tasks, such as computer vision, speech …
become powerful tools required to solve complicated tasks, such as computer vision, speech …
[HTML][HTML] Continuous emotion recognition for long-term behavior modeling through recurrent neural networks
One's internal state is mainly communicated through nonverbal cues, such as facial
expressions, gestures and tone of voice, which in turn shape the corresponding emotional …
expressions, gestures and tone of voice, which in turn shape the corresponding emotional …