Modular neural network-type CANFIS neuro-fuzzy modeling for multi-illumination color device characterization

Annual Conference of the North American Fuzzy Information Processing Society - NAFIPS

Volumn 4, Issue , 2001, Pages 2090-2095

  Mizutani, Eiji ^a   Nishio, Kenichi ^b  

^a NATIONAL TSING HUA UNIVERSITY   (Taiwan)

^b SONY CORPORATION   (Japan)

Author keywords

[No Author keywords available]

Indexed keywords

APPROXIMATION THEORY; COLOR IMAGE PROCESSING; FUZZY SETS; MATHEMATICAL MODELS; MATRIX ALGEBRA; OPTIMIZATION; VIDEO CAMERAS;

ADAPTIVE NETWORK MODELING; COLOR DEVICE CHARACTERIZATION; MODULAR NEURAL NETWORK; NEURO FUZZY MODELING;

MULTILAYER NEURAL NETWORKS;

EID: 0035792032     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (18)

1. Eiji Mizutani and Kenichi Nishio "Adaptive-Network Approaches to Multi-Illuminant Color Device Characterization of CMYG Electronic Cameras for Color Correction" In Proceedings of the 10th Sony Research Forum, pages 51-55, Tokyo JAPAN, December 15, 2000.
2. N. Katoh "Colorimetric Optimization of a NTSC Broadcast Color Video Camera" Technical Report, Munsell Color Science Laboratory, Rochester Institute Of Technology, 1992.
3. R. W. G. Hunt "Measuring color" Ellis Horwood Limited, West Sussex, England, 1991 (2nd Ed.).
4. G. Wyszecki and W. S. Stiles "Color science: Concepts and methods, quantitative data and formulae" John Wiley & Sons, New York (2nd Ed.) 1982
5. E. Mizutani, K. Nishio, N. Katoh, and M. Blasgen "Color device characterization of electronic cameras by solving adaptive networks nonlinear least squares problems" In Proceedings of the 8th IEEE International Conference on Fuzzy Systems, Vol. 2, pages 858-862, August, 1999.
6. Eiji Mizutani "Chapter 13: Coactive Neuro-Fuzzy Modeling: Toward Generalized ANFIS" In Neuro-Fuzzy and Soft Computing: a computational approach to learnig and machine intelligence (J.-S. Roger Jang, C.-T. Sun and E. Mizutani), pages 369-400 Prentice Hall, 1997.
7. E. Mizutani, J.-S. R. Jang, K. Nishio, H. Takagi, and D. M. Auslander "Coactive Neuro-Fuzzy Modeling for Color Recipe Prediction" In Proceedings of the IEEE International Conference on Neural Networks, pages 2252-2257, Perth, 1995.
8. E. Mizutani, J.-S. R. Jang, K. Nishio, H. Takagi, and D. M. Auslander "Coactive neural networks with adjustable fuzzy membership functions and their applications" In Proceedings of the International Conference on Fuzzy Logic and Neural Networks, pages 581-582, Iizuka, Japan, 1994.
9. J.-S. Roger Jang "Chapter 4: Fuzzy Inference Systems" In Neuro-Fuzzy and Soft Computing: a computational approach to learning and machine intelligence (J.-S. Roger Jang, C.-T. Sun and E. Mizutani), pages 73-91 Prentice Hall, 1997.
10. J.-S. Roger Jang "Chapter 12: ANFIS Adaptive Neuro-Fuzzy Inference Systems" In Neuro-Fuzzy and Soft Computing: a computational approach to learning and machine intelligence (J.-S. Roger Jang, C.-T. Sun and E. Mizutani), pages 335-368 Prentice Hall, 1997.
11. J.-S. Roger Jang "Chapter 19: ANFIS Applications" In Neuro-Fuzzy and Soft Computing: a computational approach to learning and machine intelligence (J.-S. Roger Jang, C.-T. Sun and E. Mizutani), pages 503-534 Prentice Hall, 1997.
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16. Eiji Mizutani and James W. Demmel "On iterative Krylov-dogleg trust-region steps for solving neural networks nonlinear least squares problems" To appear in Advances in Neural Information Processing Systems (NIPS 13), MIT Press, 2001
17. Eiji Mizutani and James W. Demmel "On generalized dogleg trust-region steps using the Krylov subspace for solving neural networks nonlinear least squares problems" In preparation for Technical Report, Dept. of Computer Science, University of California at Berkeley, 2001.
18. Eiji Mitzutani "Powell's dogleg trust-region steps with the quasi-Newton augmented Hessian for neural nonlinear least-squares learning" In Proceedings of the IEEE International Conference on Neural Networks, Vol. 2, pages 1239-1244, Washington, D.C., July, 1999