Sentiment analysis (SA) has gained much traction In the field of artificial intelligence (AI) and
natural language processing (NLP). There is growing demand to automate analysis of user …

Advances in quantitative biomarker development have accelerated new forms of data-driven
insights for patients with cancer. However, most approaches are limited to a single mode of …

Sentiment analysis is an emerging technology that aims to explore people's attitudes toward
an entity. It can be applied in a variety of different fields and scenarios, such as product …

Biomedical data are becoming increasingly multimodal and thereby capture the underlying
complex relationships among biological processes. Deep learning (DL)-based data fusion …

Multimodal Sentiment Analysis is an active area of research that leverages multimodal
signals for affective understanding of user-generated videos. The predominant approach …

Multimodal emotion recognition, that is, emotion recognition uses machine learning to
generate multi-modal features on the basis of videos which has become a research hotspot …

In this paper, we address the task of utterance level emotion recognition in conversations
using commonsense knowledge. We propose COSMIC, a new framework that incorporates …

Emotion recognition in conversation (ERC) has received much attention, lately, from
researchers due to its potential widespread applications in diverse areas, such as health …

Attention Model has now become an important concept in neural networks that has been
researched within diverse application domains. This survey provides a structured and …

With the recent success of the pre-training technique for NLP and image-linguistic tasks,
some video-linguistic pre-training works are gradually developed to improve video-text …