It is well established in psychology that humans conceptualize emotions by features known as valence (the degree of pleasantness or unpleasantness) and arousal (the intensity of bodily reactions, such ...
Abstract: This research aims to enhance the ability of computers to classify emotional states from brain signals using EEG data. Emotions are complex mental states that can significantly affect a ...
Abstract: In this paper, we proposed a novel deep learning framework, the Synergistic Deep Learning Model, for recognizing copyrighted characters with heightened accuracy and minimized overfitting.
Abstract: This paper presents a novel framework for emotion detection from electroencephalogram (EEG) signals, integrating both deep learning and traditional machine learning approaches to enhance ...
Abstract: Image emotion recognition aims to analyze and understand the emotions conveyed by images. Due to the high similarity of features between different emotion categories, the model is prone to ...
Facial Emotion Recognition System Based on Classification of Expression Patterns Using Deep Learning
Abstract: Given the wide range of facial expressions, it can be challenging to infer emotions from photos of people. Prior studies on the classification of emotions from facial photos using deep ...
Abstract: Emotion recognition plays an important role in various aspects of daily life, including education, healthcare, and entertainment. Moreover, intelligent emotion prediction enhances ...
Abstract: The objective of this work is to present a music recommendation system that personalises the suggested songs by recognising emotions from speech. The system leverages emotion extraction from ...
Abstract: In recent years, the rise of advanced machine learning techniques has led to an increase in research on brain-computer interfaces. It’s considered a multifaceted challenge to develop ...
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