A systematic review on affective computing: Emotion models, databases, and recent advances
Affective computing conjoins the research topics of emotion recognition and sentiment
analysis, and can be realized with unimodal or multimodal data, consisting primarily of …
analysis, and can be realized with unimodal or multimodal data, consisting primarily of …
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 …
Outlook on human-centric manufacturing towards Industry 5.0
The recent shift to wellbeing, sustainability, and resilience under Industry 5.0 has prompted
formal discussions that manufacturing should be human-centric–placing the wellbeing of …
formal discussions that manufacturing should be human-centric–placing the wellbeing of …
Special issue editorial: Artificial intelligence in organizations: Implications for information systems research
Artificial intelligence (AI) technologies offer novel, distinctive opportunities and pose new
significant challenges to organizations that set them apart from other forms of digital …
significant challenges to organizations that set them apart from other forms of digital …
[HTML][HTML] A systematic survey on multimodal emotion recognition using learning algorithms
Emotion recognition is the process to detect, evaluate, interpret, and respond to people's
emotional states and emotions, ranging from happiness to fear to humiliation. The COVID-19 …
emotional states and emotions, ranging from happiness to fear to humiliation. The COVID-19 …
Introducing wesad, a multimodal dataset for wearable stress and affect detection
P Schmidt, A Reiss, R Duerichen, C Marberger… - Proceedings of the 20th …, 2018 - dl.acm.org
Affect recognition aims to detect a person's affective state based on observables, with the
goal to eg improve human-computer interaction. Long-term stress is known to have severe …
goal to eg improve human-computer interaction. Long-term stress is known to have severe …
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 …
Emotion recognition from physiological signal analysis: A review
Human computer interaction is increasingly utilized in smart home, industry 4.0 and
personal health. Communication between human and computer can benefit by a flawless …
personal health. Communication between human and computer can benefit by a flawless …
Self-supervised ECG representation learning for emotion recognition
We exploit a self-supervised deep multi-task learning framework for electrocardiogram
(ECG)-based emotion recognition. The proposed solution consists of two stages of learning …
(ECG)-based emotion recognition. The proposed solution consists of two stages of learning …
Human‐computer interaction for recognizing speech emotions using multilayer perceptron classifier
AA Alnuaim, M Zakariah, PK Shukla… - Journal of …, 2022 - Wiley Online Library
Human‐computer interaction (HCI) has seen a paradigm shift from textual or display‐based
control toward more intuitive control modalities such as voice, gesture, and mimicry …
control toward more intuitive control modalities such as voice, gesture, and mimicry …