Explainable artificial intelligence of multi-level stacking ensemble for detection of Alzheimer's disease based on particle swarm optimization and the sub-scores of …
Alzheimer's disease (AD) is a progressive neurological disorder characterized by memory
loss and cognitive decline, affecting millions worldwide. Early detection is crucial for effective …
loss and cognitive decline, affecting millions worldwide. Early detection is crucial for effective …
Interpretable multimodal sentiment classification using deep multi-view attentive network of image and text data
IKS Al-Tameemi, MR Feizi-Derakhshi… - IEEE …, 2023 - ieeexplore.ieee.org
Multimodal data can convey user emotions and feelings more effectively and interactively
than unimodal content. Thus, multimodal sentiment analysis (MSA) research has recently …
than unimodal content. Thus, multimodal sentiment analysis (MSA) research has recently …
Multimodal transformer augmented fusion for speech emotion recognition
Y Wang, Y Gu, Y Yin, Y Han, H Zhang… - Frontiers in …, 2023 - frontiersin.org
Speech emotion recognition is challenging due to the subjectivity and ambiguity of emotion.
In recent years, multimodal methods for speech emotion recognition have achieved …
In recent years, multimodal methods for speech emotion recognition have achieved …
[PDF][PDF] Multi-model fusion framework using deep learning for visual-textual sentiment classification
IKS Al-Tameemi, MR Feizi-Derakhshi… - … Materials & Continua, 2023 - cdn.techscience.cn
Multimodal Sentiment Analysis (SA) is gaining popularity due to its broad application
potential. The existing studies have focused on the SA of single modalities, such as texts or …
potential. The existing studies have focused on the SA of single modalities, such as texts or …
Emotion Fusion-Sense (Emo Fu-Sense)–A novel multimodal emotion classification technique
Human emotions play a vital role in overall well-being. With the advent of advance
technologies growing interest has been observed in develo** a multimodal emotion …
technologies growing interest has been observed in develo** a multimodal emotion …
Measuring Non-Typical Emotions for Mental Health: A Survey of Computational Approaches
Analysis of non-typical emotions, such as stress, depression and engagement is less
common and more complex compared to that of frequently discussed emotions like …
common and more complex compared to that of frequently discussed emotions like …
QuMIN: quantum multi-modal data fusion for humor detection
Humour detection has attracted considerable attention due to its significance in interpreting
dialogues across text, visual, and acoustic modalities. However, effective methods to map …
dialogues across text, visual, and acoustic modalities. However, effective methods to map …
Personalized emotion analysis based on fuzzy multi-modal transformer model
Analyzing and detecting human intensions and emotions are important means to improve
the communication between users and machines in the areas of human-computer …
the communication between users and machines in the areas of human-computer …
AS-Net: active speaker detection using deep audio-visual attention
A Radman, J Laaksonen - Multimedia Tools and Applications, 2024 - Springer
Abstract Active Speaker Detection (ASD) aims at identifying the active speaker among
multiple speakers in a video scene. Previous ASD models often seek audio and visual …
multiple speakers in a video scene. Previous ASD models often seek audio and visual …
CCMA: CapsNet for audio–video sentiment analysis using cross-modal attention
H Li, A Guo, Y Li - The Visual Computer, 2024 - Springer
Multimodal sentiment analysis is a challenging research area that aims to investigate the
use of complementary multimodal information to analyze the sentiment tendencies of a …
use of complementary multimodal information to analyze the sentiment tendencies of a …