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Combinatorial Fusion Analysis in Brain Informatics: Gender Variation in Facial Attractiveness Judgment

Hsu, D. Frank and Ito, Takehito and Schweikert, Christina and Matsuda, Tetsuya and Shimojo, Shinsuke (2011) Combinatorial Fusion Analysis in Brain Informatics: Gender Variation in Facial Attractiveness Judgment. In: Brain Informatics. Lecture Notes in Computer Science. No.6889. Springer , Berlin, pp. 2-20. ISBN 9783642236044. https://resolver.caltech.edu/CaltechAUTHORS:20200522-134411712

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Abstract

Information processing in the brain or other decision making systems, such as in multimedia, involves fusion of information from multiple sensors, sources, and systems at the data, feature or decision level. Combinatorial Fusion Analysis (CFA), a recently developed information fusion paradigm, uses a combinatorial method to model the decision space and the Rank-Score Characteristic (RSC) function to measure cognitive diversity. In this paper, we first introduce CFA and its practice in a variety of application domains such as computer vision and target tracking, information retrieval and Internet search, and virtual screening and drug discovery. We then apply CFA to investigate gender variation in facial attractiveness judgment on three tasks: liking, beauty and mentalization using RSC function. It is demonstrated that the RSC function is useful in the differentiation of gender variation and task judgment, and hence can be used to complement the notion of correlation which is widely used in statistical decision making. In addition, it is shown that CFA is a viable approach to deal with various issues and problems in brain informatics.


Item Type:Book Section
Related URLs:
URLURL TypeDescription
https://doi.org/10.1007/978-3-642-23605-1_2DOIArticle
https://rdcu.be/b4lCUPublisherFree ReadCube access
Additional Information:© 2011 Springer-Verlag Berlin Heidelberg. TM was supported by the Japanese University Global Centers of Excellence Program of the Japanese Ministry of Education, Culture, Sports, and Technology. SS was supported by Core Research for Evolutional Science and Technology, the Japanese Science and Technology Agency.
Funders:
Funding AgencyGrant Number
Ministry of Education, Culture, Sports, Science and Technology (MEXT)UNSPECIFIED
Japan Science and Technology Agency (JST)UNSPECIFIED
Subject Keywords:Virtual Screening; Rank Function; Target Tracking; Information Fusion; Cognitive Diversity
Series Name:Lecture Notes in Computer Science
Issue or Number:6889
Record Number:CaltechAUTHORS:20200522-134411712
Persistent URL:https://resolver.caltech.edu/CaltechAUTHORS:20200522-134411712
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:103426
Collection:CaltechAUTHORS
Deposited By: Tony Diaz
Deposited On:22 May 2020 21:07
Last Modified:22 May 2020 21:07

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