Journal of Engineering and Applied Sciences

Year: 2017
Volume: 12
Issue: 20
Page No. 5332 - 5337

Colorimeter Using Artificial Neural Networks

Authors : Laura Pramparo and Robinson Jimenez Moreno

References

Abdel-Hamid, O., A.R. Mohamed, H. Jiang, L. Deng and G. Penn et al., 2014. Convolutional neural networks for speech recognition. IEEE. ACM. Trans. Audio Speech lang. Process., 22: 1533-1545.
CrossRef  |  Direct Link  |  

Cardei, V.C., 2000. A neural network approach to colour constancy. Ph.D Thesis, Simon Fraser University, Burnaby, British Columbia.

Demuth, H.B., M.H. Beale, D.O. Jess and M.T. Hagan, 2014. Neural Network Design. 2nd Edn., Martin Hagan, USA., ISBN:0971732116,.

Golomb, B.A., D.T. Lawrence and T.J. Sejnowski, 1991. Sexnet: A neural network identifies sex from human face. Adv. Neural Inform. Process. Syst., 3: 572-577.

Krizhevsky, A., I. Sutskever and G.E. Hinton, 2012. Imagenet Classification with Deep Convolutional Neural Networks. In: Advances in Neural Information Processing Systems, Leen, T.K., G.D. Thomas and T. Volker (Eds.). MIT Press, Cambridge, Massachusetts, USA., ISBN:0-262-12241-3, pp: 1097-1105.

Liu, W., Z. Wang, X. Liu, N. Zeng and Y. Liu et al., 2017. A survey of deep neural network architectures and their applications. Neurocomputing, 234: 11-26.
Direct Link  |  

Ming-Jung, S., V. Deepthi and V.K. Asari, 2003. Neural network based skin color model for face detection. Proceedings of the 32nd Applied Imagery Pattern Recognition Workshop, Oct. 15-17, IEEE Computer Society, USA., pp: 141-145.

Nose-Filho, K., A.D.P. Lotufo and C.R. Minussi, 2011. Preprocessing data for short-term load forecasting with a general regression neural network and a moving average filter. Proceedings of the 2011 IEEE International Conference on PowerTech Trondheim, June 19-23, 2011, IEEE, Trondheim, Norway, ISBN: 978-1-4244-8419-5, pp: 1-7.

Phung, S.L., A. Bouzerdoum and D. Chai, 2005. Skin segmentation using color pixel classification: analysis and comparison. IEEE. Trans. Pattern Anal. Mach. Intell., 27: 148-154.
CrossRef  |  Direct Link  |  

Riedmiller, M. and H. Braun, 1993. A direct adaptive method for faster backpropagation learning: The RPROP algorithm. IEEE Int. Conf. Neural Networks, 1: 586-591.

Rowley, H.A., S. Baluja and T. Kanade, 1998. Neural network-based face detection. Pattern Anal. Mach. Intell., 20: 23-28.
CrossRef  |  

Sercu, T., C. Puhrsch, B. Kingsbury and Y. LeCun, 2016. Very deep multilingual convolutional neural networks for LVCSR. Proceedings of the 2016 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), March 20-25, 2016, IEEE, Shanghai, China, ISBN:978-1-4799-9988-0, pp: 4955-4959.

Simard, P.Y., D. Steinkraus and J.C. Platt, 2003. Best practices for convolutional neural networks applied to visual document analysis. Proceedings of the of 7th International Conference on Document Analysis and Recognition ICDAR Vol. 3, August 3-6, 2003, IEEE, New York, USA., pp: 958-962.

Simonyan, K. and A. Zisserman, 2014. Very deep convolutional networks for large-scale image recognition. Master Thesis, Cornell University, Ithaca, New York.

Stathopoulou, I.O. and G.A. Tsihrintzis, 2004. An improved neural-network-based face detection and facial expression classification system. Proceedings of the 2004 IEEE International Conference on Systems, Man and Cybernetics Vol. 1, October 10-13, 2004, IEEE, Hague, Netherlands, ISBN:0-7803-8566-7, pp: 666-671.

Zeiler, M.D. and R. Fergus, 2014. Visualizing and understanding convolutional networks. Proceedings of the European Conference on Computer Vision, September 6-12, 2014, Springer, Zurich, Switzerland, pp: 818-833.

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