In this book, the problem of object recognition and reconstruction is addressed using image moments. We discussed a Artificial Neural Network (ANN) based scheme for Object recognition. The invariance properties of geometric moments as well as lower order moments corresponding to partially occluded objects are used to train a feedforward ANN. The trained neural network is used to predict the actual moments from the moments of the object with different occlusions. The object is recognized based on the comparison of the actual moments and the predicted moments. The problem of object reconstruction using Zernike and Pseudo- zernike moments is also discussed.
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Vendeur : BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Allemagne
Taschenbuch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -In this book, the problem of object recognition and reconstruction is addressed using image moments. We discussed a Artificial Neural Network (ANN) based scheme for Object recognition. The invariance properties of geometric moments as well as lower order moments corresponding to partially occluded objects are used to train a feedforward ANN. The trained neural network is used to predict the actual moments from the moments of the object with different occlusions. The object is recognized based on the comparison of the actual moments and the predicted moments. The problem of object reconstruction using Zernike and Pseudo- zernike moments is also discussed. 88 pp. Englisch. N° de réf. du vendeur 9783838325163
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Vendeur : moluna, Greven, Allemagne
Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: DUTTA SAIBALMr.Saibal Dutta received BE degree in Elect & Comm Engg from Burdwan University, India in 2005 and M. Tech degree in Elect. syst. and Comm. Engg. from N.I.T, Rourkela, India in 2007. Dr.Pradipta Kumar Nanda is Prof an. N° de réf. du vendeur 5413161
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Vendeur : buchversandmimpf2000, Emtmannsberg, BAYE, Allemagne
Taschenbuch. Etat : Neu. This item is printed on demand - Print on Demand Titel. Neuware -In this book, the problem of object recognition and reconstruction is addressed using image moments. We discussed a Artificial Neural Network (ANN) based scheme for Object recognition. The invariance properties of geometric moments as well as lower order moments corresponding to partially occluded objects are used to train a feedforward ANN. The trained neural network is used to predict the actual moments from the moments of the object with different occlusions. The object is recognized based on the comparison of the actual moments and the predicted moments. The problem of object reconstruction using Zernike and Pseudo- zernike moments is also discussed.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 88 pp. Englisch. N° de réf. du vendeur 9783838325163
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Vendeur : Revaluation Books, Exeter, Royaume-Uni
Paperback. Etat : Brand New. 88 pages. 8.66x5.91x0.20 inches. In Stock. N° de réf. du vendeur __3838325168
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Vendeur : AHA-BUCH GmbH, Einbeck, Allemagne
Taschenbuch. Etat : Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - In this book, the problem of object recognition and reconstruction is addressed using image moments. We discussed a Artificial Neural Network (ANN) based scheme for Object recognition. The invariance properties of geometric moments as well as lower order moments corresponding to partially occluded objects are used to train a feedforward ANN. The trained neural network is used to predict the actual moments from the moments of the object with different occlusions. The object is recognized based on the comparison of the actual moments and the predicted moments. The problem of object reconstruction using Zernike and Pseudo- zernike moments is also discussed. N° de réf. du vendeur 9783838325163
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Vendeur : preigu, Osnabrück, Allemagne
Taschenbuch. Etat : Neu. MOMENT BASED OBJECT RECOGNITION AND RECONSTRUCTION | Theory and Applications | Saibal Dutta (u. a.) | Taschenbuch | 88 S. | Englisch | 2012 | LAP LAMBERT Academic Publishing | EAN 9783838325163 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu. N° de réf. du vendeur 101381969
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