This book includes a fingerprint indexing scheme at feature level fusion based on Minutiae Vicinity and Minutiae Cylindrical Code and the classifying them using the SVM and K-means classifier, proving which is more efficient, which will improve the efficiency in seeking a candidate reference list from large scale biometric data databases, where the personality related with the input data is dictated by contrasting it with each and every entry in the database. This coordinating procedure is tedious and conceivably increments, the rate of wrong identification, hence we propose a new fingerprint indexing approach which would improve the performance of the system.
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Librería: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Alemania
Taschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book includes a fingerprint indexing scheme at feature level fusion based on Minutiae Vicinity and Minutiae Cylindrical Code and the classifying them using the SVM and K-means classifier, proving which is more efficient, which will improve the efficiency in seeking a candidate reference list from large scale biometric data databases, where the personality related with the input data is dictated by contrasting it with each and every entry in the database. This coordinating procedure is tedious and conceivably increments, the rate of wrong identification, hence we propose a new fingerprint indexing approach which would improve the performance of the system. 96 pp. Englisch. Nº de ref. del artículo: 9786202563376
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Kartoniert / Broschiert. Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Kadam Pooja ShreeMrs. Pooja Shree Kadam completed ME in computer engineering from sigma institute of engineering and technology Vadodara, BE from Vadodara Institute of Engineering, Kotambi, waghodia. She is currently working as tempo. Nº de ref. del artículo: 494826462
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Taschenbuch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - This book includes a fingerprint indexing scheme at feature level fusion based on Minutiae Vicinity and Minutiae Cylindrical Code and the classifying them using the SVM and K-means classifier, proving which is more efficient, which will improve the efficiency in seeking a candidate reference list from large scale biometric data databases, where the personality related with the input data is dictated by contrasting it with each and every entry in the database. This coordinating procedure is tedious and conceivably increments, the rate of wrong identification, hence we propose a new fingerprint indexing approach which would improve the performance of the system. Nº de ref. del artículo: 9786202563376
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Taschenbuch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -This book includes a fingerprint indexing scheme at feature level fusion based on Minutiae Vicinity and Minutiae Cylindrical Code and the classifying them using the SVM and K-means classifier, proving which is more efficient, which will improve the efficiency in seeking a candidate reference list from large scale biometric data databases, where the personality related with the input data is dictated by contrasting it with each and every entry in the database. This coordinating procedure is tedious and conceivably increments, the rate of wrong identification, hence we propose a new fingerprint indexing approach which would improve the performance of the system.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 96 pp. Englisch. Nº de ref. del artículo: 9786202563376
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Taschenbuch. Condición: Neu. A Fingerprint Indexing and Classification For Biometric Database | Fingerprint Indexing and Classification | Pooja Shree Kadam (u. a.) | Taschenbuch | 96 S. | Englisch | 2020 | LAP LAMBERT Academic Publishing | EAN 9786202563376 | Verantwortliche Person für die EU: LAP Lambert Academic Publishing, Brivibas Gatve 197, 1039 RIGA, LETTLAND, customerservice[at]vdm-vsg[dot]de | Anbieter: preigu Print on Demand. Nº de ref. del artículo: 118723876
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