Multimodal classification: Current landscape, taxonomy and future directions
Multimodal classification research has been gaining popularity with new datasets in
domains such as satellite imagery, biometrics, and medicine. Prior research has shown the …
domains such as satellite imagery, biometrics, and medicine. Prior research has shown the …
Video sentiment analysis with bimodal information-augmented multi-head attention
T Wu, J Peng, W Zhang, H Zhang, S Tan, F Yi… - Knowledge-Based …, 2022 - Elsevier
Humans express feelings or emotions via different channels. Take language as an example,
it entails different sentiments under different visual–acoustic contexts. To precisely …
it entails different sentiments under different visual–acoustic contexts. To precisely …
Attention-based multi-modal sentiment analysis and emotion detection in conversation using RNN
The availability of an enormous quantity of multimodal data and its widespread applications,
automatic sentiment analysis and emotion classification in the conversation has become an …
automatic sentiment analysis and emotion classification in the conversation has become an …
TeFNA: Text-centered fusion network with crossmodal attention for multimodal sentiment analysis
Multimodal sentiment analysis (MSA), which goes beyond the analysis of texts to include
other modalities such as audio and visual data, has attracted a significant amount of …
other modalities such as audio and visual data, has attracted a significant amount of …
A soft voting ensemble learning-based approach for multimodal sentiment analysis
It is possible to determine people's feelings and opinions about a subject or product from
social media posts via sentiment analysis. With the pervasive usage of the Internet and …
social media posts via sentiment analysis. With the pervasive usage of the Internet and …
AdaMoW: Multimodal sentiment analysis based on adaptive modality-specific weight fusion network
J Zhang, X Wu, C Huang - IEEE Access, 2023 - ieeexplore.ieee.org
Multimodal sentiment analysis (MSA) is a crucial task in the field of natural language
processing (NLP), with a wide range of applications. This paper proposes an adaptive …
processing (NLP), with a wide range of applications. This paper proposes an adaptive …
Novel OGBEE-based feature selection and feature-level fusion with MLP neural network for social media multimodal sentiment analysis
Numerous public networks, namely Instagram, YouTube, Facebook, Twitter, etc., share their
own feelings and idea as videotapes, posts, and pictures. In future research, adapting to …
own feelings and idea as videotapes, posts, and pictures. In future research, adapting to …
Predicting semantic category of answers for question answering systems using transformers: a transfer learning approach
A question-answering (QA) system is a key application in the field of natural language
processing (NLP) that provides relevant answers to user queries written in natural language …
processing (NLP) that provides relevant answers to user queries written in natural language …
Emotion Recognition of College Students Based on Audio and Video Image.
C Zhu, T Ding, X Min - Traitement du Signal, 2022 - search.ebscohost.com
Emotional problems are common among contemporary college students. To improve their
mental health, it is urgent to quickly identify college students' negative emotions, and guide …
mental health, it is urgent to quickly identify college students' negative emotions, and guide …
Multimodal sentiment analysis based on nonverbal representation optimization network and contrastive interaction learning
Z Quan, T Sun, M Su, J Wei, X Zhang… - … on Systems, Man, and …, 2022 - ieeexplore.ieee.org
Multimodal sentiment analysis is an active subfield of natural language processing. It aims to
extract and integrate semantic information gathered from multiple modalities to identify the …
extract and integrate semantic information gathered from multiple modalities to identify the …