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CIM 2013 : Special Issue on Computational Intelligence and Affective Computing in IEEE Computational Intelligence Magazine | |||||||||||||||
Link: http://cis.ieee.org/ieee-computational-intelligence-magazine.html | |||||||||||||||
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Call For Papers | |||||||||||||||
The IEEE Computational Intelligence Society Affective Computing Task Force was recently established to promote this emerging and exciting research direction. We are organizing a Special Issue on “Computational Intelligence and Affective Computing” in the IEEE Computational Intelligence Magazine (CIM) to present the state-of-the-art research focusing on applying CI algorithms to affective computing problems, and applying affective computing concepts to developing novel CI algorithms.
http://cis.ieee.org/ieee-computational-intelligence-magazine.html Call for Papers IEEE Computational Intelligence Magazine (CIM): Special Issue on Computational Intelligence and Affective Computing Affective computing is “computing that relates to, arises from, or deliberately influences emotions,” as initially coined by Professor R. Picard (Media Lab, MIT). It has been gaining popularity rapidly in the last decade because it has great potential in the next generation of human-computer interfaces. One goal of affective computing is to design a computer system that responds in a rational and strategic fashion to real-time changes in user affect (e.g., happiness, sadness), cognition (e.g., frustration, boredom) and motivation, as represented by for example speech, facial expressions, physiological signals, and neurocognitive performance. Affective computing raises many new challenges for signal processing, modeling, and information aggregation. Especially, the body signals used for affect recognition are very noisy and subject-dependent. Computational intelligence (CI) methods, including fuzzy sets and systems, neural networks, and evolutionary algorithms, may be used to build intuitive and robust emotion recognition algorithms. Further, emotions, which are intrinsic to human beings, may also inspire some new CI algorithms, just like human brains inspired neural networks and survival of the fittest in nature inspired evolutionary computation. The IEEE Computational Intelligence Society Affective Computing Task Force was recently established to promote this emerging and exciting research direction. We are organizing a Special Issue on “Computational Intelligence and Affective Computing” in the IEEE Computational Intelligence Magazine (CIM) to present the state-of-the-art research focusing on applying CI algorithms to affective computing problems, and applying affective computing concepts to developing novel CI algorithms. The topics of interest include but are not limited to: * Emotion-inspired CI algorithms. * Computational models and architecture for processing emotions and other affective states. * Automatic emotion recognition and synthesis from physiological signals, facial expressions, body language, speech, or neurocognitive performance. * Emotion mining from texts, images, or other media. * Affective interaction with digital systems, virtual agents and robots. * Applications of affective computing in personalized learning, affective gaming, affective robotics, virtual reality, social networking, smart environments, healthcare and behavioral informatics, etc. Note that all submissions to this special issue must be within the scope of CI. About IEEE CIM: IEEE CIM is IEEE Computational Intelligence Society’s flagship magazine distributed to its over 7000 members. According to the latest Thomson Reuters Journal Citation Report, IEEE CIM had an impact factor of 3.368 in 2011. It is ranked 15th among all 133 IEEE transactions and magazines, and 8th out of 111 journals under Compute Science and Artificial Intelligence. Important Dates: Manuscript Deadline: October 15, 2012 Notice of Review: November 15, 2012 Final Manuscript Due: December 15, 2012 Intended Issue of Publication: May 2013 Manuscript Submission: Authors should send their PDF file (10-14 pages in IEEE Transactions double-column format) to either guest editor by email. All papers will be rigorously peer reviewed by experts in the field. Guest Editors: Dr. Dongrui Wu Machine Learning Lab, GE Global Research, NY USA drwu09@gmail.com Dr. Christian Wagner School of Computer Science, University of Nottingham, UK Christian.Wagner@nottingham.ac.uk Deadline: 15 October 2012 |
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