Harnessing multimodal data integration to advance precision oncology
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 …
insights for patients with cancer. However, most approaches are limited to a single mode of …
Systematic reviews in sentiment analysis: a tertiary study
A Ligthart, C Catal, B Tekinerdogan - Artificial intelligence review, 2021 - Springer
With advanced digitalisation, we can observe a massive increase of user-generated content
on the web that provides opinions of people on different subjects. Sentiment analysis is the …
on the web that provides opinions of people on different subjects. Sentiment analysis is the …
Detecting fake news by exploring the consistency of multimodal data
During the outbreak of the new Coronavirus (2019-nCoV) in 2020, the spread of fake news
has caused serious social panic. Fake news often uses multimedia information such as text …
has caused serious social panic. Fake news often uses multimedia information such as text …
Cross-modal multitask transformer for end-to-end multimodal aspect-based sentiment analysis
As an emerging task in opinion mining, End-to-End Multimodal Aspect-Based Sentiment
Analysis (MABSA) aims to extract all the aspect-sentiment pairs mentioned in a pair of …
Analysis (MABSA) aims to extract all the aspect-sentiment pairs mentioned in a pair of …
Deep learning-based multimodal emotion recognition from audio, visual, and text modalities: A systematic review of recent advancements and future prospects
S Zhang, Y Yang, C Chen, X Zhang, Q Leng… - Expert Systems with …, 2023 - Elsevier
Emotion recognition has recently attracted extensive interest due to its significant
applications to human-computer interaction. The expression of human emotion depends on …
applications to human-computer interaction. The expression of human emotion depends on …
[PDF][PDF] Performance evaluation and comparison using deep learning techniques in sentiment analysis
AP Pandian - Journal of Soft Computing Paradigm (JSCP), 2021 - scholar.archive.org
One of the most common applications of deep learning algorithms is sentiment analysis.
This study delivers a better performing and efficient automated feature extraction technique …
This study delivers a better performing and efficient automated feature extraction technique …
Ensemble transfer learning-based multimodal sentiment analysis using weighted convolutional neural networks
Huge amounts of multimodal content and comments in a mixture form of text, image, and
emoji are continuously shared by users on various social networks. Most of the comments of …
emoji are continuously shared by users on various social networks. Most of the comments of …
A novel method for sentiment classification of drug reviews using fusion of deep and machine learning techniques
Nowadays, the development of new computer-based technologies has led to rapid increase
in the volume of user-generated textual content on the website. Patient-written medical and …
in the volume of user-generated textual content on the website. Patient-written medical and …
Natural language processing in law: Prediction of outcomes in the higher courts of Turkey
Natural language processing (NLP) based approaches have recently received attention for
legal systems of several countries. It is of interest to study the wide variety of legal systems …
legal systems of several countries. It is of interest to study the wide variety of legal systems …
Multimodal cyberbullying detection using capsule network with dynamic routing and deep convolutional neural network
A Kumar, N Sachdeva - Multimedia Systems, 2022 - Springer
Cyberbullying is the use of information technology networks by individuals' to humiliate,
tease, embarrass, taunt, defame and disparage a target without any face-to-face contact …
tease, embarrass, taunt, defame and disparage a target without any face-to-face contact …