Non-Linear Weighted Averaging for Multimodal Information Fusion by Employing Analytical Network Process

Date

2012-11-15

Author

Yilmaz, Turgay
Yazıcı, Adnan
Kitsuregawa, Masaru

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Linear combination is a popular approach in information fusion due to its simplicity. However, it suffers from the performance upper-bound of linearity and dependency on the selection of weights. In this study, we introduce a 'simple' alternative for linear combination, which is a non-linear extension on it. The approach is based on the Analytical Network Process, which is a popular approach in Operational Research, but never applied for fusion before. The approach benefits from two major ideas; interdependency between classes and dependency of classes on the features. Experiments conducted on CCV dataset demonstrate that proposed approach outperforms linear combination and other simple approaches, moreover it is less-dependent on the selection of weights.

Subject Keywords

Accuracy, Support vector machines, Ear, Multimedia communication, Educational institutions, Linearity, Training

URI

https://hdl.handle.net/11511/53842

Collections

Department of Computer Engineering, Conference / Seminar

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Citation Formats

T. Yilmaz, A. Yazıcı, and M. Kitsuregawa, “Non-Linear Weighted Averaging for Multimodal Information Fusion by Employing Analytical Network Process,” 2012, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/53842.