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 …
Deep learning-based multimodal emotion recognition from audio, visual, and text modalities: A systematic review of recent advancements and future prospects
S Zhang, Y Yang, C Chen, X Zhang, Q Leng… - Expert Systems with …, 2023 - Elsevier
Emotion recognition has recently attracted extensive interest due to its significant
applications to human-computer interaction. The expression of human emotion depends on …
applications to human-computer interaction. The expression of human emotion depends on …
A survey of textual emotion recognition and its challenges
Textual language is the most natural carrier of human emotion. In natural language
processing, textual emotion recognition (TER) has become an important topic due to its …
processing, textual emotion recognition (TER) has become an important topic due to its …
[HTML][HTML] Emerging technologies for smart cities' transportation: geo-information, data analytics and machine learning approaches
KLM Ang, JKP Seng, E Ngharamike… - … International Journal of …, 2022 - mdpi.com
With the recent increase in urban drift, which has led to an unprecedented surge in urban
population, the smart city (SC) transportation industry faces a myriad of challenges …
population, the smart city (SC) transportation industry faces a myriad of challenges …
[HTML][HTML] Exploring the frontiers of deep learning and natural language processing: A comprehensive overview of key challenges and emerging trends
In the recent past, more than 5 years or so, DL especially the large language models (LLMs)
has generated extensive studies out of a distinctly average downturn field of knowledge …
has generated extensive studies out of a distinctly average downturn field of knowledge …
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 …
[HTML][HTML] Sentiment analysis on images using convolutional neural networks based Inception-V3 transfer learning approach
Sentiment analysis has become a precious tool for businesses because it can be used in so
many ways: to find out what customers think about products and services, to build customer …
many ways: to find out what customers think about products and services, to build customer …
Big data analytics deep learning techniques and applications: A survey
HA Selmy, HK Mohamed, W Medhat - Information Systems, 2023 - Elsevier
Deep learning (DL), as one of the most active machine learning research fields, has
achieved great success in numerous scientific and technological disciplines, including …
achieved great success in numerous scientific and technological disciplines, including …
A review of multimodal emotion recognition from datasets, preprocessing, features, and fusion methods
B Pan, K Hirota, Z Jia, Y Dai - Neurocomputing, 2023 - Elsevier
Affective computing is one of the most important research fields in modern human–computer
interaction (HCI). The goal of affective computing is to study and develop the theories …
interaction (HCI). The goal of affective computing is to study and develop the theories …
Adaptive multimodal emotion detection architecture for social robots
J Heredia, E Lopes-Silva, Y Cardinale… - Ieee …, 2022 - ieeexplore.ieee.org
Emotion recognition is a strategy for social robots used to implement better Human-Robot
Interaction and model their social behaviour. Since human emotions can be expressed in …
Interaction and model their social behaviour. Since human emotions can be expressed in …