[HTML][HTML] A short survey on deep learning for multimodal integration: Applications, future perspectives and challenges
GM Dimitri - Computers, 2022 - mdpi.com
Deep learning has achieved state-of-the-art performances in several research applications
nowadays: from computer vision to bioinformatics, from object detection to image …
nowadays: from computer vision to bioinformatics, from object detection to image …
SKEAFN: sentiment knowledge enhanced attention fusion network for multimodal sentiment analysis
Multimodal sentiment analysis is an active research field that aims to recognize the user's
sentiment information from multimodal data. The primary challenge in this field is to develop …
sentiment information from multimodal data. The primary challenge in this field is to develop …
Capsule network-based deep ensemble transfer learning for multimodal sentiment analysis
A Ghorbanali, MK Sohrabi - Expert Systems with Applications, 2024 - Elsevier
Understanding the attitudes of users about different topics through their huge amount of
comments and opinions on social networks is an emerging hot issue. Analyzing the …
comments and opinions on social networks is an emerging hot issue. Analyzing the …
Multimodal negative sentiment recognition of online public opinion on public health emergencies based on graph convolutional networks and ensemble learning
Z Zeng, S Sun, Q Li - Information Processing & Management, 2023 - Elsevier
To improve the effect of multimodal negative sentiment recognition of online public opinion
on public health emergencies, we constructed a novel multimodal fine-grained negative …
on public health emergencies, we constructed a novel multimodal fine-grained negative …
Advanced Fraud Detection in Blockchain Transactions: An Ensemble Learning and Explainable AI Approach
In recent years, cryptocurrencies have experienced rapid growth and adoption,
revolutionizing the financial sector. However, the rise of digital currencies has also led to an …
revolutionizing the financial sector. However, the rise of digital currencies has also led to an …
Image-text fusion transformer network for sarcasm detection
J Liu, S Tian, L Yu, X Shi, F Wang - Multimedia Tools and Applications, 2024 - Springer
Sarcasm is a sophisticated method to convey ideas. Usually, the literal meaning of a
sarcasm message is the opposite of its true intent. The development of social platforms has …
sarcasm message is the opposite of its true intent. The development of social platforms has …
Dual-channel prototype network for few-shot pathology image classification
In the field of pathology, the scarcity of certain diseases and the difficulty of annotating
images hinder the development of large, high-quality datasets, which in turn affects the …
images hinder the development of large, high-quality datasets, which in turn affects the …
Deep ensemble transfer learning framework for COVID-19 Arabic text identification via deep active learning and text data augmentation
Since the declaration of COVID-19 as an epidemic by the World Health Organization in
September 2019, the task of monitoring and managing the spread of misinformation related …
September 2019, the task of monitoring and managing the spread of misinformation related …
Knowledge-integrated Multi-modal Movie Turning Point Identification
D Wang, R Xu, L Cheng, Z Wang - ACM Transactions on Multimedia …, 2024 - dl.acm.org
The rapid development of artificial intelligence provides rich technologies and tools for the
automated understanding of literary works. As a comprehensive carrier of storylines, movies …
automated understanding of literary works. As a comprehensive carrier of storylines, movies …
Deep learning based features extraction for facial gender classification using ensemble of machine learning technique
F Waris, F Da, S Liu - Multimedia Systems, 2024 - Springer
Accurate and efficient gender recognition is an essential for many applications such as
surveillance, security, and biometrics. Recently, deep learning techniques have made …
surveillance, security, and biometrics. Recently, deep learning techniques have made …