Multimodal sentiment analysis leveraging the strength of deep neural networks enhanced by the XGBoost classifier-Reference-Cited by-同舟云学术

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Multimodal sentiment analysis leveraging the strength of deep neural networks enhanced by the XGBoost classifier

Published:2024-02-10 Issue: Volume: Page:1-23
ISSN:1025-5842
Container-title:Computer Methods in Biomechanics and Biomedical Engineering
language:en
Short-container-title:Computer Methods in Biomechanics and Biomedical Engineering

Author:

Chandrasekaran Ganesh¹,Dhanasekaran S.²,Moorthy C.³,Arul Oli A.⁴

Affiliation:

1. Department of Computer and Communication Engineering, Sri Eshwar College of Engineering, Coimbatore, Tamil Nadu, India

2. Department of Electronics and Communication Engineering, Sri Eshwar College of Engineering, Coimbatore, Tamil Nadu, India

3. Department of Electronics and Communication Engineering, Dr. Mahalingam College of Engineering and Technology, Pollachi, Tamil Nadu, India

4. Department of Computer Science Engineering, Saveetha Engineering College, Chennai, Tamil Nadu, India

Publisher

Informa UK Limited

Link

https://www.tandfonline.com/doi/pdf/10.1080/10255842.2024.2313066

Reference40 articles.

1. Multimodal Video Sentiment Analysis Using Deep Learning Approaches, a Survey

2. Multimodal Emotion Recognition using Deep Learning

3. Interpretable Multimodal Sentiment Classification Using Deep Multi-View Attentive Network of Image and Text Data

4. Multimodal sentiment analysis using reliefF feature selection and random forest classifier

5. Attention-based multimodal sentiment analysis and emotion recognition using deep neural networks

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. A novel socio-pragmatic framework for sentiment analysis in Dravidian–English code-switched texts;Knowledge-Based Systems;2024-09

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