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 …
Multi-sensor information fusion based on machine learning for real applications in human activity recognition: State-of-the-art and research challenges
This paper firstly introduces common wearable sensors, smart wearable devices and the key
application areas. Since multi-sensor is defined by the presence of more than one model or …
application areas. Since multi-sensor is defined by the presence of more than one model or …
Feature dimensionality reduction: a review
W Jia, M Sun, J Lian, S Hou - Complex & Intelligent Systems, 2022 - Springer
As basic research, it has also received increasing attention from people that the “curse of
dimensionality” will lead to increase the cost of data storage and computing; it also …
dimensionality” will lead to increase the cost of data storage and computing; it also …
A survey on deep learning in medicine: Why, how and when?
New technologies are transforming medicine, and this revolution starts with data. Health
data, clinical images, genome sequences, data on prescribed therapies and results …
data, clinical images, genome sequences, data on prescribed therapies and results …
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 comprehensive review of speech emotion recognition systems
During the last decade, Speech Emotion Recognition (SER) has emerged as an integral
component within Human-computer Interaction (HCI) and other high-end speech processing …
component within Human-computer Interaction (HCI) and other high-end speech processing …
[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 …
Contrastive representation learning for electroencephalogram classification
Interpreting and labeling human electroencephalogram (EEG) is a challenging task
requiring years of medical training. We present a framework for learning representations …
requiring years of medical training. We present a framework for learning representations …
Feature-level fusion approaches based on multimodal EEG data for depression recognition
This study aimed to construct a novel multimodal model by fusing different
electroencephalogram (EEG) data sources, which were under neutral, negative and positive …
electroencephalogram (EEG) data sources, which were under neutral, negative and positive …
Emotion recognition from EEG signal focusing on deep learning and shallow learning techniques
Recently, electroencephalogram-based emotion recognition has become crucial in enabling
the Human-Computer Interaction (HCI) system to become more intelligent. Due to the …
the Human-Computer Interaction (HCI) system to become more intelligent. Due to the …