Cognitive information processing (CIP) currently plays important roles in many applications such as attention, encoding, memory, artificial intelligence (AI), and cognitive computing latest advances in machine thinking. As well as the characteristics of the human visual system, its information and limitations must be first clearly studied, and the artificial systems should be then developed. In this session, we discuss the wide range topics of human cognitive functions, advancements, limitations, and possibility for artificial system development. The topics of interests that fascinating area of this session, but are not limited to, as follows:
• Human Cognition: this involves insights into how humans perceive, process, and store information. By understanding these cognitive processes, designers of AI systems can develop interfaces that align with natural human cognition, making interactions more intuitive and user-friendly.
• Natural Language Processing (NLP): Leveraging CIP in AI HMI often involves advancements in NLP. Understanding how humans process and comprehend language allows AI systems to communicate more effectively with users, whether through speech recognition, chatbots, or natural language interfaces.
• UI/UX Design: Considering principles of attention from CIP, AI interfaces can be designed to prioritize information effectively, ensuring that users' attention is directed toward important elements. This is crucial for designing user interfaces that facilitate efficient information processing.
• Emotion Recognition: Understanding human emotions, a facet of cognitive processing, is important for creating emotionally intelligent AI systems. AI can be designed to recognize and respond to human emotions, enhancing the overall quality of interaction.
• Human-Machine Interaction (HMI): The integration of biomedical eye tracking and body movement in HMI aims to enhance the communication and interaction between humans and machines, particularly in the context of understanding and responding to human physiological signals.
• Biomedical Information Processing: Advanced techniques for processing and analyzing biomedical images and signals. This is crucial for applications such as medical imaging, signal processing for physiological data, and monitoring of various health parameters.
Special Session Co-chairs:
• Watanabe Katsumi, Waseda University, Japan
• Roberto Caldara, University of Fribourg, Switzerland
• Montri Phothisonothai, Kasetsart University, Thailand
Submission link: https://edas.info/newPaper.php?c=31104&track=122965