Ever wonder why chatting with AI feels comforting? Discover why asking AI feels rewarding and why our brains keep coming back ...

Abstract: Electroencephalography (EEG)-based emotion recognition is essential for medical assistance and human-computer interaction. Although deep learning-based emotion recognition methods have ...

Abstract: Existing approaches often operate poorly in noisy or occluded conditions, rely on cloud-based inference subject to latency and privacy issues, and do not take emotional context into ...

Abstract: Facial emotion recognition has played a significant role in applications of artificial intelligence, enabling the detection and recognition of human facial emotions for diverse societal ...

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 ...

Abstract: Emotion intensity recognition is important for understanding mental states and improving human-computer interaction. Recently, electroencephalogram (EEG)-based spectrogram analysis was ...

Introduction: Physiological signals offer a significant advantage in the field of emotion recognition due to their objective nature, as they are less susceptible to volitional control and thus provide ...

CNN in deep learning is a special type of neural network that can understand images and visual information. It works just like human vision: first it detects edges, lines and then recognizes faces and ...

Abstract: Identifying the emotions hidden in speech (SER) encounters difficulties in virtue of the subjective and variable nature of human emotions, along with limitations such as data dependency, ...