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IEEE COGMI 2023 : 5th IEEE International Conference on Cognitive Machine Intelligence | |||||||||||||||
Link: http://www.sis.pitt.edu/lersais/conference/cogmi/2023/ | |||||||||||||||
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Call For Papers | |||||||||||||||
The goal of the IEEE Conference on Cognitive Machine Intelligence (IEEE CogMI) is to create a research and development forum on cognitive machine intelligence to foster research results on AI and ML with cognitive science and behavioral science. It promotes productive collaborations among experts from multiple disciplines, such as but not limited to: computer science, electronic and computer engineering, information science, economics, industrial engineering, psychology, social and behavioral sciences, biological and physical sciences, and ethics, law and policy. IEEE CogMI aims to be a premier, highly multidisciplinary forum to foster interaction and exchange of innovative ideas, and collaboration among researchers, practitioners, philosophers from academia, industry and government sectors who are interested in developing innovative AI/ML algorithms, applications and systems by integrating cognitive science and putting humans in the loop, promoting innovations in cognitive machine intelligence.
Topics Topics of interest are broadly from the area of machine intelligence, behavior and cognition, and include, but are not limited to, the following: Artificial Intelligence – theory and application Machine learning, neural networks and deep learning AI and Machine cognition Human-machine collaboration Human-robot interaction Neuromorphic computing Probabilistic Computing Machine behavior: bias, fairness, transparency, accountability, robustness, etc. Robotics and autonomous systems, and process automation Computer vision & image processing/recognition AI-optimized hardware and software Natural language processing/generation, text analytics and speech recognition Recommendation and reputation systems Virtual agents, chatbots, and conversational robots Computational mechanism design, algorithmic game theory and multi-agent systems Trust and Privacy in AI/ML and Deep Learning & Adversarial Machine Learning Decision support and management AI in application domains: Business & Finance, Health/Public Health, Transportation, Manufacturing, Media/Social media, Science & Engineering, Education, Social-welfare and well-being, etc. AI in Edge/Fog/Cloud computing, Internet of Things, and Cyber Physical Systems |
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