CoAR-Maze: empowering children’s collaborative tangible programming in augmented reality
Authors (first, second and last of 5)
Collection
Both-AI-and-Cognition-Driven Human-Machine Synergy
In recent years, the intelligent level of human-computer interaction has advanced significantly, but it is still far from meeting users’ needs . In particular, the model, system, algorithm, structure, application, and societal influence of equality between humans and computers and high-level collaboration, such as "cognition," "interaction," "security," and "inclusiveness" continues to set significant obstacles. A major turning point in the study of intelligent human-computer interaction technology may be how to blend machine AI and human cognition to create a new paradigm of natural human-computer interaction. Additionally, it is anticipated to advance the field of human-computer integration to a high degree while providing core engines for paramount manufacturing, medical rehabilitation, education and entertainment, social services, smart home appliances, and other industries. This special issue provides an opportunity for researchers and system developers to address research challenges of Human-Machine Synergy through the combination of machine’s AI and human’s cognition. We encourage authors to make contributions from different fields related to pervasive sensing and interactions, to cognitive structure and mechanism of synergy, task dynamic division and operation, behavior recognition and scene understanding, human-computer interaction, CSCW, learning algorithms and models, application prototype and use studies. Papers on theoretical, practical, and methodological issues in both-AI-and-cognition-driven human-machine synergy are welcome.
Editors
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Zhiquan Feng
Affiliation: University of Jinan, China Email: ise_fengzq@ujn.edu.cn
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Danli Wang
Affiliation: Institute of Automation, Chinese Academy of Sciences Email: danli.wang@ia.ac.cn
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Liang He
Affiliation: Purdue University, USA Email: he731@purdue.edu
