Neural networks : the official journal of the International Neural Network Society
Jul 27, 2024
As one of the most important tasks of natural language processing, textual emotion classification (TEC) aims to recognize and detect all emotions contained in texts. However, most existing methods are implemented using deep learning approaches, which...
Anthropomorphized robots are increasingly integrated into human social life, playing vital roles across various fields. This study aimed to elucidate the neural dynamics underlying users' perceptual and emotional responses to robots with varying leve...
Affect recognition in a real-world, less constrained environment is the principal prerequisite of the industrial-level usefulness of this technology. Monitoring the psychological profile using smart, wearable electroencephalogram (EEG) sensors during...
Virtual reality (VR) technology is often referred to as the 'ultimate empathy machine' due to its capability to immerse users in alternate perspectives and environments beyond their immediate physical reality. In this study, participants will be imme...
The rise of social media has changed how people view connections. Machine Learning (ML)-based sentiment analysis and news categorization help understand emotions and access news. However, most studies focus on complex models requiring heavy resources...
In empirical art research, understanding how viewers judge visual artworks as beautiful is often explored through the study of attributes-specific inherent characteristics or artwork features such as color, complexity, and emotional expressiveness. T...
IEEE transactions on neural networks and learning systems
Jul 8, 2024
A coupled multimodal emotional feature analysis (CMEFA) method based on broad-deep fusion networks, which divide multimodal emotion recognition into two layers, is proposed. First, facial emotional features and gesture emotional features are extracte...
IEEE transactions on neural networks and learning systems
Jul 8, 2024
Neuropsychological studies suggest that co-operative activities among different brain functional areas drive high-level cognitive processes. To learn the brain activities within and among different functional areas of the brain, we propose local-glob...
IEEE transactions on neural networks and learning systems
Jul 8, 2024
Decoding emotional states from human brain activity play an important role in the brain-computer interfaces. Existing emotion decoding methods still have two main limitations: one is only decoding a single emotion category from a brain activity patte...
The cognitive state of a person can be categorized using the circumplex model of emotional states, a continuous model of two dimensions: arousal and valence. The purpose of this research is to select a machine learning model(s) to be integrated into ...
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