Coactive neuro-fuzzy modeling for color recipe prediction

Eiji Mizutan, Jyh Shing R. Jang, Kenichi Nishio, Hideyuki Takagi, David M. Auslander

Research output: Contribution to conferencePaper

7 Citations (Scopus)

Abstract

We explore neuro-fuzzy approaches to computerized color recipe prediction, which relates surface spectral reflectance of a target color to several colorant proportions. The approaches are expressed within the framework of CANFIS (CoActive Neuro-Fuzzy Inference System) where both Neural Networks (NNs) and Fuzzy Systems (FSs) play active roles together in pursuit of a given task. To find an ideal adaptive model for this problem, we have investigated a variety of structures: they feature knowledge-embedded architectures and an adaptive FS, which serves to determine color selection. They have enormous potential for augmenting prediction capability.

Original languageEnglish
Pages2252-2257
Number of pages6
Publication statusPublished - Dec 1 1995
Externally publishedYes
EventProceedings of the 1995 IEEE International Conference on Neural Networks. Part 1 (of 6) - Perth, Aust
Duration: Nov 27 1995Dec 1 1995

Other

OtherProceedings of the 1995 IEEE International Conference on Neural Networks. Part 1 (of 6)
CityPerth, Aust
Period11/27/9512/1/95

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All Science Journal Classification (ASJC) codes

  • Software

Cite this

Mizutan, E., Jang, J. S. R., Nishio, K., Takagi, H., & Auslander, D. M. (1995). Coactive neuro-fuzzy modeling for color recipe prediction. 2252-2257. Paper presented at Proceedings of the 1995 IEEE International Conference on Neural Networks. Part 1 (of 6), Perth, Aust, .