Coactive neuro-fuzzy modeling for color recipe prediction

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

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 conference › Paper › peer-review

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 language	English
Pages	2252-2257
Number of pages	6
Publication status	Published - 1995
Externally published	Yes
Event	Proceedings of the 1995 IEEE International Conference on Neural Networks. Part 1 (of 6) - Perth, Aust Duration: Nov 27 1995 → Dec 1 1995

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Other	Proceedings of the 1995 IEEE International Conference on Neural Networks. Part 1 (of 6)
City	Perth, Aust
Period	11/27/95 → 12/1/95

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Software

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title = "Coactive neuro-fuzzy modeling for color recipe prediction",

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.",

author = "Eiji Mizutan and Jang, {Jyh Shing R.} and Kenichi Nishio and Hideyuki Takagi and Auslander, {David M.}",

year = "1995",

language = "English",

pages = "2252--2257",

note = "Proceedings of the 1995 IEEE International Conference on Neural Networks. Part 1 (of 6) ; Conference date: 27-11-1995 Through 01-12-1995",

}

TY - CONF

T1 - Coactive neuro-fuzzy modeling for color recipe prediction

AU - Mizutan, Eiji

AU - Jang, Jyh Shing R.

AU - Nishio, Kenichi

AU - Takagi, Hideyuki

AU - Auslander, David M.

PY - 1995

Y1 - 1995

N2 - 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.

AB - 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.

UR - http://www.scopus.com/inward/record.url?scp=0029461473&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=0029461473&partnerID=8YFLogxK

M3 - Paper

AN - SCOPUS:0029461473

SP - 2252

EP - 2257

T2 - Proceedings of the 1995 IEEE International Conference on Neural Networks. Part 1 (of 6)

Y2 - 27 November 1995 through 1 December 1995

ER -

Coactive neuro-fuzzy modeling for color recipe prediction

Abstract

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