Ethiopian Banknote Denomination Classification & Fake Detection System: An optimal feature extraction and classification technique - Couverture souple

Alene, Asfaw

9786200095398: Ethiopian Banknote Denomination Classification & Fake Detection System: An optimal feature extraction and classification technique

Couverture souple

ISBN 10 : 6200095396 ISBN 13 : 9786200095398

Editeur : LAP LAMBERT Academic Publishing, 2019

Afficher les exemplaires de cette �dition comportant l?ISBN

0 D'occasion

8 Neuf

De EUR 54,90

D�tails de l'�dition

�diteur: LAP LAMBERT Academic Publishing
Date d'�dition: 2019
Langue: anglais
ISBN 10: 6200095396
ISBN 13: 9786200095398
Reliure: Broch�
Nombre de pages: 124
Coordonn�es du fabricant: non disponible
Personne responsable: KreGa Onlinehandel GmbH
4950000000000
info@krega-onlinehandel.de

Birkenweg 31
Brakel
33034
Allemagne

R�sultats de recherche pour Ethiopian Banknote Denomination Classification &...

Image fournie par le vendeur

Ethiopian Banknote Denomination Classification & Fake Detection System

Asfaw Alene

Edit� par LAP LAMBERT Academic Publishing Nov 2019, 2019

ISBN 10 : 6200095396 ISBN 13 : 9786200095398

Neuf Taschenbuch

impression � la demande

Vendeur : BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Allemagne

�valuation du vendeur 5 sur 5 �toiles

Taschenbuch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Forgery is one of the critical problems affecting cash transactions. Forged banknotes are becoming serious threats hampering the smooth transactions in Ethiopia. Hence, the availability of such fake notes in the market needs the automation of the money transaction system. The banking industries are unable to fully utilize self-serving devices including ATMs intensively. Nevertheless, banks have not yet utilized a reliable recognition system to identify forged banknotes. This calls for the development of a better authenticity verification system. In this study, we have examined the color momentum, SIFT, GLCM, combination of SIFT, color, and GLCM, and convolutional neural network as a feature extraction technique and support vector machine, K- nearest neighbor classifier, and feed-forward artificial neural network as a classifier to design Ethiopian banknote recognition system. In order to minimize the effect of noisy data, we have employed an intensive image preprocessing tasks, like image histogram equalization and adaptive median filter-based image denoising. 124 pp. Englisch. N� de r�f. du vendeur 9786200095398

Contacter le vendeur

Acheter neuf

EUR 54,90

Exp�dition �EUR 23
Exp�dition depuis Allemagne vers Etats-Unis

Quantit� disponible : 2 disponible(s)

Ajouter au panier

Image d'archives

Ethiopian Banknote Denomination Classification & Fake Detection System: An optimal feature extraction and classification technique

Alene, Asfaw

Edit� par LAP LAMBERT Academic Publishing, 2019

ISBN 10 : 6200095396 ISBN 13 : 9786200095398

Neuf Couverture souple

impression � la demande

Vendeur : Majestic Books, Hounslow, Royaume-Uni

�valuation du vendeur 4 sur 5 �toiles

Etat : New. Print on Demand. N� de r�f. du vendeur 400144016

Contacter le vendeur

Acheter neuf

EUR 84,82

Exp�dition �EUR 7,53
Exp�dition depuis Royaume-Uni vers Etats-Unis

Quantit� disponible : 4 disponible(s)

Ajouter au panier

Image d'archives

Ethiopian Banknote Denomination Classification & Fake Detection System: An optimal feature extraction and classification technique

Alene, Asfaw

Edit� par LAP LAMBERT Academic Publishing, 2019

ISBN 10 : 6200095396 ISBN 13 : 9786200095398

Neuf Couverture souple

Vendeur : Books Puddle, New York, NY, Etats-Unis

�valuation du vendeur 4 sur 5 �toiles

Etat : New. N� de r�f. du vendeur 26397281615

Contacter le vendeur

Acheter neuf

EUR 89,15

Exp�dition �EUR 3,44
Exp�dition nationale�: Etats-Unis

Quantit� disponible : 4 disponible(s)

Ajouter au panier

Image fournie par le vendeur

Ethiopian Banknote Denomination Classification & Fake Detection System

Asfaw Alene

Edit� par LAP LAMBERT Academic Publishing, 2019

ISBN 10 : 6200095396 ISBN 13 : 9786200095398

Neuf Couverture souple

Vendeur : moluna, Greven, Allemagne

�valuation du vendeur 5 sur 5 �toiles

Etat : New. N� de r�f. du vendeur 497104766

Contacter le vendeur

Acheter neuf

EUR 45,45

Exp�dition �EUR 48,99
Exp�dition depuis Allemagne vers Etats-Unis

Quantit� disponible : Plus de 20 disponibles

Ajouter au panier

Image d'archives

Ethiopian Banknote Denomination Classification & Fake Detection System: An optimal feature extraction and classification technique

Alene, Asfaw

Edit� par LAP LAMBERT Academic Publishing, 2019

ISBN 10 : 6200095396 ISBN 13 : 9786200095398

Neuf Couverture souple

impression � la demande

Vendeur : Biblios, Frankfurt am main, HESSE, Allemagne

�valuation du vendeur 4 sur 5 �toiles

Etat : New. PRINT ON DEMAND. N� de r�f. du vendeur 18397281605

Contacter le vendeur

Acheter neuf

EUR 89,70

Exp�dition �EUR 9,95
Exp�dition depuis Allemagne vers Etats-Unis

Quantit� disponible : 4 disponible(s)

Ajouter au panier

Image fournie par le vendeur

Ethiopian Banknote Denomination Classification & Fake Detection System

Asfaw Alene

Edit� par LAP LAMBERT Academic Publishing Nov 2019, 2019

ISBN 10 : 6200095396 ISBN 13 : 9786200095398

Neuf Taschenbuch

impression � la demande

Vendeur : buchversandmimpf2000, Emtmannsberg, BAYE, Allemagne

�valuation du vendeur 5 sur 5 �toiles

Taschenbuch. Etat : Neu. This item is printed on demand - Print on Demand Titel. Neuware -Forgery is one of the critical problems affecting cash transactions. Forged banknotes are becoming serious threats hampering the smooth transactions in Ethiopia. Hence, the availability of such fake notes in the market needs the automation of the money transaction system. The banking industries are unable to fully utilize self-serving devices including ATMs intensively. Nevertheless, banks have not yet utilized a reliable recognition system to identify forged banknotes. This calls for the development of a better authenticity verification system. In this study, we have examined the color momentum, SIFT, GLCM, combination of SIFT, color, and GLCM, and convolutional neural network as a feature extraction technique and support vector machine, K- nearest neighbor classifier, and feed-forward artificial neural network as a classifier to design Ethiopian banknote recognition system. In order to minimize the effect of noisy data, we have employed an intensive image preprocessing tasks, like image histogram equalization and adaptive median filter-based image denoising.VDM Verlag, Dudweiler Landstra�e 99, 66123 Saarbr�cken 124 pp. Englisch. N� de r�f. du vendeur 9786200095398

Contacter le vendeur

Acheter neuf

EUR 54,90

Exp�dition �EUR 60
Exp�dition depuis Allemagne vers Etats-Unis

Quantit� disponible : 1 disponible(s)

Ajouter au panier

Image fournie par le vendeur

Ethiopian Banknote Denomination Classification & Fake Detection System : An optimal feature extraction and classification technique

Asfaw Alene

Edit� par LAP LAMBERT Academic Publishing, 2019

ISBN 10 : 6200095396 ISBN 13 : 9786200095398

Neuf Taschenbuch

impression � la demande

Vendeur : AHA-BUCH GmbH, Einbeck, Allemagne

�valuation du vendeur 5 sur 5 �toiles

Taschenbuch. Etat : Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Forgery is one of the critical problems affecting cash transactions. Forged banknotes are becoming serious threats hampering the smooth transactions in Ethiopia. Hence, the availability of such fake notes in the market needs the automation of the money transaction system. The banking industries are unable to fully utilize self-serving devices including ATMs intensively. Nevertheless, banks have not yet utilized a reliable recognition system to identify forged banknotes. This calls for the development of a better authenticity verification system. In this study, we have examined the color momentum, SIFT, GLCM, combination of SIFT, color, and GLCM, and convolutional neural network as a feature extraction technique and support vector machine, K- nearest neighbor classifier, and feed-forward artificial neural network as a classifier to design Ethiopian banknote recognition system. In order to minimize the effect of noisy data, we have employed an intensive image preprocessing tasks, like image histogram equalization and adaptive median filter-based image denoising. N� de r�f. du vendeur 9786200095398

Contacter le vendeur

Acheter neuf

EUR 55,56

Exp�dition �EUR 61,02
Exp�dition depuis Allemagne vers Etats-Unis

Quantit� disponible : 1 disponible(s)

Ajouter au panier

Image fournie par le vendeur

Ethiopian Banknote Denomination Classification & Fake Detection System | An optimal feature extraction and classification technique

Asfaw Alene

Edit� par LAP LAMBERT Academic Publishing, 2019

ISBN 10 : 6200095396 ISBN 13 : 9786200095398

Neuf Taschenbuch

impression � la demande

Vendeur : preigu, Osnabr�ck, Allemagne

�valuation du vendeur 5 sur 5 �toiles

Taschenbuch. Etat : Neu. Ethiopian Banknote Denomination Classification & Fake Detection System | An optimal feature extraction and classification technique | Asfaw Alene | Taschenbuch | Englisch | 2019 | LAP LAMBERT Academic Publishing | EAN 9786200095398 | Verantwortliche Person f�r die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabr�ck, mail[at]preigu[dot]de | Anbieter: preigu Print on Demand. N� de r�f. du vendeur 120468865

Contacter le vendeur

Acheter neuf

EUR 47,20

Exp�dition �EUR 70
Exp�dition depuis Allemagne vers Etats-Unis

Quantit� disponible : 5 disponible(s)

Ajouter au panier