Deep learning (DL) is revolutionizing evidence-based decision-making techniques that can
be applied across various sectors. Specifically, it possesses the ability to utilize two or more …

The rapid growth of Internet-based applications, such as social media platforms and blogs,
has resulted in comments and reviews concerning day-to-day activities. Sentiment analysis …

Affective computing conjoins the research topics of emotion recognition and sentiment
analysis, and can be realized with unimodal or multimodal data, consisting primarily of …

Sentiment analysis has been a well-studied research direction in computational linguistics.
Deep neural network models, including convolutional neural networks (CNN) and recurrent …

Sentiment analysis, one of the research hotspots in the natural language processing field,
has attracted the attention of researchers, and research papers on the field are increasingly …

Deep learning--based models have surpassed classical machine learning--based
approaches in various text classification tasks, including sentiment analysis, news …

Sentiment analysis is an emerging trend nowadays to understand people's sentiments in
multiple situations in their quotidian life. Social media data would be utilized for the entire …

Generalized zero-shot learning (GZSL) aims to train a model for classifying data samples
under the condition that some output classes are unknown during supervised learning. To …

Abstract Undoubtedly, coronavirus (COVID-19) has caused one of the biggest challenges of
all times. The ongoing COVID-19 pandemic has caused more than 150 million infected …

Accurate automated medical image recognition, including classification and segmentation,
is one of the most challenging tasks in medical image analysis. Recently, deep learning …