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IEEE Transactions on Affective Computing is a peer-reviewed journal published by IEEE, covering Emotion and Mood Recognition, Sentiment Analysis and Opinion Mining, EEG and Brain-Computer Interfaces. Over its lifetime it has published 1,700 papers, which have received 88,713 citations.
| Publisher | IEEE |
|---|---|
| Reference style | Numbered (IEEE) Numbered — [1], [2] in the text [1] A. Smith, B. Jones, and C. Lee, "A representative article title," IEEE Transactions on Affective Computing, vol. 12, no. 3, pp. 45–58, 2023.
Formats any DOI in IEEE Transactions on Affective Computing style. No sign-up. |
| Publishes research in | Emotion and Mood Recognition Sentiment Analysis and Opinion Mining EEG and Brain-Computer Interfaces Face and Expression Recognition Face recognition and analysis |
| ISSN | 1949-3045 |
| Citation impact (2-yr) | 5.07 |
| h-index | 133 |
| i10-index | 917 |
| Top institutions publishing here | Tsinghua University |
| Journal website | ieeexplore.ieee.org |
| You get | A submission-ready PDF and the editable LaTeX source — ready to submit. |
Citations each year’s papers have accumulated so far — the most recent years are still building up.
We present a multimodal data set for the analysis of human affective states. The electroencephalogram (EEG) and peripheral physiological signals of 32 participants were recorded as each watched 40 one-minute long excerpts of music videos. Participants rated each video in terms of the levels of arousal, valence, like/dislike, dominance, and familiarity. For 22 of the…
Automated affective computing in the wild setting is a challenging problem in computer vision. Existing annotated databases of facial expressions in the wild are small and mostly cover discrete emotions (aka the categorical model). There are very limited annotated facial databases for affective computing in the continuous dimensional model (e.g., valence and arousal). To meet…
This survey describes recent progress in the field of Affective Computing (AC), with a focus on affect detection. Although many AC researchers have traditionally attempted to remain agnostic to the different emotion theories proposed by psychologists, the affective technologies being developed are rife with theoretical assumptions that impact their effectiveness. Hence, an informed and integrated…
Work on voice sciences over recent decades has led to a proliferation of acoustic parameters that are used quite selectively and are not always extracted in a similar fashion. With many independent teams working in different research areas, shared standards become an essential safeguard to ensure compliance with state-of-the-art methods allowing appropriate comparison of results…
With the transition of facial expression recognition (FER) from laboratory-controlled to challenging in-the-wild conditions and the recent success of deep learning techniques in various fields, deep neural networks have increasingly been leveraged to learn discriminative representations for automatic FER. Recent deep FER systems generally focus on two important issues: overfitting caused by a lack of…
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