Deep learning for depression recognition with audiovisual cues: A review
With the acceleration of the pace of work and life, people are facing more and more
pressure, which increases the probability of suffering from depression. However, many …
pressure, which increases the probability of suffering from depression. However, many …
[HTML][HTML] Facial expression recognition using computer vision: A systematic review
Emotion recognition has attracted major attention in numerous fields because of its relevant
applications in the contemporary world: marketing, psychology, surveillance, and …
applications in the contemporary world: marketing, psychology, surveillance, and …
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 …
Depaudionet: An efficient deep model for audio based depression classification
This paper presents a novel and effective audio based method on depression classification.
It focuses on two important issues,\emph {ie} data representation and sample imbalance …
It focuses on two important issues,\emph {ie} data representation and sample imbalance …
Avec 2014: 3d dimensional affect and depression recognition challenge
Mood disorders are inherently related to emotion. In particular, the behaviour of people
suffering from mood disorders such as unipolar depression shows a strong temporal …
suffering from mood disorders such as unipolar depression shows a strong temporal …
Transformer-based multimodal feature enhancement networks for multimodal depression detection integrating video, audio and remote photoplethysmograph signals
Depression stands as one of the most widespread psychological disorders and has
garnered increasing attention. Currently, how to effectively achieve automatic multimodal …
garnered increasing attention. Currently, how to effectively achieve automatic multimodal …
Exploiting multi-cnn features in cnn-rnn based dimensional emotion recognition on the omg in-the-wild dataset
D Kollias, S Zafeiriou - IEEE Transactions on Affective …, 2020 - ieeexplore.ieee.org
This article presents a novel CNN-RNN based approach, which exploits multiple CNN
features for dimensional emotion recognition in-the-wild, utilizing the One-Minute Gradual …
features for dimensional emotion recognition in-the-wild, utilizing the One-Minute Gradual …
Visually interpretable representation learning for depression recognition from facial images
Recent evidence in mental health assessment have demonstrated that facial appearance
could be highly indicative of depressive disorder. While previous methods based on the …
could be highly indicative of depressive disorder. While previous methods based on the …
Automatic depression recognition using CNN with attention mechanism from videos
Artificial intelligence (AI) has incorporated various automatic systems and frameworks to
diagnose the severity of depression using hand-crafted features. However, process of …
diagnose the severity of depression using hand-crafted features. However, process of …
[HTML][HTML] Automated depression analysis using convolutional neural networks from speech
L He, C Cao - Journal of biomedical informatics, 2018 - Elsevier
To help clinicians to efficiently diagnose the severity of a person's depression, the affective
computing community and the artificial intelligence field have shown a growing interest in …
computing community and the artificial intelligence field have shown a growing interest in …