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Identifying emotions from facial expressions using a deep convolutional neural network-based approach
Sentiment identification on facial expression is an interesting study domain with applications in various disciplines, including security, health,...
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A multimodal sentiment analysis approach for tweets by comprehending co-relations between information modalities
With the popularity of smart devices and online social media platforms, people are expressing their views in various modalities like text, images,...
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Weakly supervised discriminate enhancement network for visual sentiment analysis
Several methods employ weakly supervised technology to highlight the visual sentiment information in images, so as to improve the performance of...
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Novelty fused image and text models based on deep neural network and transformer for multimodal sentiment analysis
The rapid growth of various online platforms has made it easier than ever for people to share their feelings or opinions in the form of both textual...
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A context-sensitive multi-tier deep learning framework for multimodal sentiment analysis
One of the most appealing multidisciplinary research areas in Artificial Intelligence (AI) is Sentiment Analysis (SA). Due to the intricate and...
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Polarity-aware attention network for image sentiment analysis
Image sentiment analysis aims to employ a computational model to automatically discover the implied emotions from the underlying image, which are...
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Computational Emotion Analysis From Images: Recent Advances and Future Directions
Emotions are usually evoked in humans by images. Recently, extensive research efforts have been dedicated to understanding the emotions of images. In...
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Multi-granularity Feature Attention Fusion Network for Image-Text Sentiment Analysis
Multi-modal sentiment analysis of images and texts in social media has surpassed traditional text-based analysis and attracted more and more...
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Analytical Approach for Sentiment Analysis of Movie Reviews Using CNN and LSTM
With the rapid growth of technology and easier access to the internet, several forums like Twitter, Facebook, Instagram, etc., have come up,...
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Affective image recognition with multi-attribute knowledge in deep neural networks
Incorporating visual attributes such as objects and scene features into deep models has been proved valuable for affective image recognition. In...
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A Novel Framework for Multimodal Twitter Sentiment Analysis Using Feature Learning
Over the years there has been a lot of speculation with respect to single modal sentiment analysis of twitter (which is one of the world’s largest...
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A New Approach for Counting and Identification of Students Sentiments in Online Virtual Environments Using Convolutional Neural Networks
In this paper, we discuss the importance of counting students and the identification of their sentiments using convolutional networks, specifically...
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Visual sentiment analysis using data-augmented deep transfer learning techniques
The use of visual content to express emotions on social media platforms has become increasingly popular. Visual sentiment analysis can be used to...
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Weakly Supervised Interaction Discovery Network for Image Sentiment Analysis
Visual sentiment is subjective and abstract, and it is very challenging to locate the sentiment features from images accurately. Some researchers...
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A large-scale television advertising dataset for detailed impression analysis
Creating impressive video content such as movies and advertisements is a very important yet challenging task in business that requires both a sense...
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Compound Label Learning for Affective Image Content Analysis
The single label of an affective image cannot well reflect the emotions underneath, thus converting the single label into compound affective labels...
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Learning multi-level representations for affective image recognition
Images can convey intense affective experiences and affect people on an affective level. With the prevalence of online pictures and videos,...
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Going Beyond Closed Sets: A Multimodal Perspective for Video Emotion Analysis
Emotion analysis plays a crucial role in understanding video content. Existing studies often approach it as a closed set classification task, which...
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Learning to compose diversified prompts for image emotion classification
Image emotion classification (IEC) aims to extract the abstract emotions evoked in images. Recently, language-supervised methods such as contrastive...
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Automatic Sentiment Labelling of Multimodal Data
This study investigates the challenging problem of automatically providing sentiment labels for training and testing multimodal data containing both...