Abstract
Over past decades, Artificial Neural Network (ANN) area has been the focal point of an ever-increasing number of research works and a very active pivot of interdisciplinary research activity. It is now time to state if ANN are ready to defeat nowadays’ real-world and industrial challenges. The main goal of this paper is to present, through some of main ANN models and based techniques, their capability in real world industrial dilemmas solution. Examples of real world and industrial applications have been presented and discussed.
This is a preview of subscription content, log in via an institution to check access.
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Madani, K.: On ANN Based Solutions for Real-World Industrial Requirements. In: Rutkowski, L., Siekmann, J.H., Tadeusiewicz, R., Zadeh, L.A. (eds.) ICAISC 2004. LNCS (LNAI), vol. 3070, pp. 79–90. Springer, Heidelberg (2004)
Egmont-Petersen, M., de Ridder, D., Handels, H.: Image Processing with Neural Networks - A Review. Pattern Recognition 35, 2279–2301 (2002)
Reyneri, L.M.: Weighted Radial Basis Functions for Improved Pattern Recognition and Signal Processing. Neural Processing Let. 2(3), 2–6 (1995)
Madani, K., DeTremiolles, G., Tanhoff, P.: Image processing using RBF like neural networks: A ZISC-036 based fully parallel implementation solving real world and real complexity industrial problems. J. of Applied Intelligence (18), 195–231 (2003)
Voiry, M., Houbre, F., Amarger, V., Madani, K.: Toward Surface Imperfections Diagnosis Using Optical Microscopy Imaging in Industrial Environment. In: IAR & ACD Workshop 2005 Proceedings, pp. 139–144 (2005)
Madani, K., Voiry, M., Amarger, V., Kanaoui, N., Chohra, A., Houbre, F.: Computer Aided Diagnosis Using Soft-Computing Techniques and Image’s Issued Representation : Application to Biomedical and Industrial Fields. Computing, Special Issue on Intelligent Computing 5(3), 43–53 (2006)
Choksuriwong, A., Laurent, H., Emile, B.: Comparison of invariant descriptors for object recognition. In: IEEE International Conference on Image Processing (ICIP), pp. 377–380 (2005)
Demartines, Hérault, J.: CCA: Curvilinear Component Analysis. In: Proceedings of 15th workshop GRETSI (1995)
Lee, J.A., Lendasse, A., Donckers, N., Verleysen, M.: A Robust Nonlinear Projection Method. In: European Symposium on Artificial Neural Networks - ESANN 2000 (2000)
Sabourin, C., Madani, K., Bruneau, O.: “A Fuzzy-CMAC Based Hybrid Intuitive Approach for Biped Robot’s Adaptive Dynamic Walking”. In: Proc. ICNNAI 2006 Conference Proceedings, Brest, Belarus, May 31 - June 2, pp. 78–83 (2006)
Albus, J.S.: A new approach to manipulator control, the Cerebellar Model Articulation Controller (CMAC). Journal of Dynamic Systems, Measurement and Control, 220–227 (1975)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2009 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Madani, K., Amarger, V., Sabourin, C. (2009). ANN Based Solutions: It Is Time to Defeat Real-World and Industrial Dilemmas. In: Cabestany, J., Sandoval, F., Prieto, A., Corchado, J.M. (eds) Bio-Inspired Systems: Computational and Ambient Intelligence. IWANN 2009. Lecture Notes in Computer Science, vol 5517. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-02478-8_166
Download citation
DOI: https://doi.org/10.1007/978-3-642-02478-8_166
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-02477-1
Online ISBN: 978-3-642-02478-8
eBook Packages: Computer ScienceComputer Science (R0)