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Please use this identifier to cite or link to this item: http://eprint.iitd.ac.in/handle/2074/998

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dc.contributor.authorGanotra, Dinesh-
dc.contributor.authorJoseph, Joby-
dc.contributor.authorSingh, Kehar-
dc.date.accessioned2005-12-21T03:25:18Z-
dc.date.available2005-12-21T03:25:18Z-
dc.date.issued2002-
dc.identifier.citationOptics Communications, 202(1-3), 61-68en
dc.identifier.urihttp://eprint.iitd.ac.in/dspace/handle/2074/998-
dc.description.abstractUse of neural networks (NNs) and diffraction pattern sampling by a ring–wedge detector leads to easier and faster algorithms for pattern recognition. An estimation was made of the optimum dimensions of a digital ring–wedge detector for sampling Fourier transform of random matrices through simulation of digital ring–wedge detector. The modulus squared Fourier transforms of facial images were sampled by ring–wedge geometry, and used for training a neural net for multi-face recognition. Fourier spectral intensities obtained by simulation and experiment were both tested for training and generalization of the network which was studied as a function of learning rate and number of epochs.en
dc.format.extent315848 bytes-
dc.format.mimetypeapplication/pdf-
dc.language.isoenen
dc.subjectNeural networksen
dc.subjectFace recognitionen
dc.subjectRing–wedge detectoren
dc.titleNeural network based face recognition by using diffraction pattern sampling with a digital ring–wedge detectoren
dc.typeArticleen
Appears in Collections:Physics

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