Abstract: Most existing emotion recognition studies rely on discrete stimulus paradigms under controlled laboratory conditions, failing to capture the inherently dynamic and transitional nature of ...

Emotion-detecting AI bridges human feelings and technology, offering benefits while sparking important debates on privacy and ethical use. Pixabay, Alexandra_Koch Emotion AI, also known as affective ...

The accurate detection of Alzheimer's disease (AD), a progressive and irreversible neurodegenerative disorder, remains a critical challenge in clinical neuroscience. The research aims to develop an ...

As shopping becomes more visually driven, imagery plays a central role in how people evaluate products. Images and videos can unfurl complex stories in an instant, making them powerful tools for ...

Though artificial intelligence is fueling a surge in synthetic child abuse images, it’s also being tested as a way to stop harm to real victims. Generative AI has enabled the production of child ...

Abstract: Music emotion recognition (MER) is an essential branch in music information retrieval, focusing on categorization of music based on emotional content. This study introduces a multimodal deep ...

Multimodal perception is essential for enabling robots to understand and interact with complex environments and human users by integrating diverse sensory data, such as vision, language, and tactile ...

🥉Top-2 Solution for the $1^{st}$ MultiModal Deception Detection (MMDD) Challenge at the $1^{st}$ Workshop on Subtle Visual Computing (SVC) All participants must sign an agreement before accessing the ...

Multimodal sentiment analysis (MSA) is an emerging technology that seeks to digitally automate extraction and prediction of human sentiments from text, audio, and video. With advances in deep learning ...

Professor Okada uses the science of social signals to improve human-AI interaction. His research explores multimodal social signals such as gaze, gestures, and voice tone of AI users to develop ...