[HTML][HTML] Emotion recognition and artificial intelligence: A systematic review (2014–2023) and research recommendations
Emotion recognition is the ability to precisely infer human emotions from numerous sources
and modalities using questionnaires, physical signals, and physiological signals. Recently …
and modalities using questionnaires, physical signals, and physiological signals. Recently …
[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 …
Emotion recognition in EEG signals using deep learning methods: A review
Emotions are a critical aspect of daily life and serve a crucial role in human decision-making,
planning, reasoning, and other mental states. As a result, they are considered a significant …
planning, reasoning, and other mental states. As a result, they are considered a significant …
Emotion recognition from unimodal to multimodal analysis: A review
K Ezzameli, H Mahersia - Information Fusion, 2023 - Elsevier
The omnipresence of numerous information sources in our daily life brings up new
alternatives for emotion recognition in several domains including e-health, e-learning …
alternatives for emotion recognition in several domains including e-health, e-learning …
A review on methods and applications in multimodal deep learning
Deep Learning has implemented a wide range of applications and has become increasingly
popular in recent years. The goal of multimodal deep learning (MMDL) is to create models …
popular in recent years. The goal of multimodal deep learning (MMDL) is to create models …
Multimodal Emotion Recognition with deep learning: advancements, challenges, and future directions
In recent years, affective computing has become a topic of considerable interest, driven by
its ability to enhance several domains, such as mental health monitoring, human–computer …
its ability to enhance several domains, such as mental health monitoring, human–computer …
A novel facial emotion recognition model using segmentation VGG-19 architecture
Abstract Facial Emotion Recognition (FER) has gained popularity in recent years due to its
many applications, including biometrics, detection of mental illness, understanding of human …
many applications, including biometrics, detection of mental illness, understanding of human …
Recent advances and trends in multimodal deep learning: A review
Deep Learning has implemented a wide range of applications and has become increasingly
popular in recent years. The goal of multimodal deep learning is to create models that can …
popular in recent years. The goal of multimodal deep learning is to create models that can …
Capsule neural networks on spatio-temporal EEG frames for cross-subject emotion recognition
Scalp EEG plots are plots of scalp potentials against time, and hence, capture spatial
information, owing to the placement of electrodes on the scalp, as well as, temporal …
information, owing to the placement of electrodes on the scalp, as well as, temporal …
多模态的情感分析技术综述.
刘继明， 张培翔， 刘颖， 张伟东… - Journal of Frontiers of …, 2021 - search.ebscohost.com
情感分析是指利用计算机自动分析确定人们所要表达的情感, 其在人机交互和刑侦破案等领域都
能发挥重大作用. 深度学习和传统特征提取算法的进步为利用多种模态进行情感分析提供了条件 …
能发挥重大作用. 深度学习和传统特征提取算法的进步为利用多种模态进行情感分析提供了条件 …