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ISBN 10: 3845407972 ISBN 13: 9783845407975
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Añadir al carritoCondición: New. pp. 184.
Idioma: Inglés
Publicado por LAP LAMBERT Academic Publishing, 2011
ISBN 10: 3845407972 ISBN 13: 9783845407975
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Añadir al carritoTaschenbuch. Condición: Neu. Detection and classification of HMV | seismic sensor | Bhopendra Singh (u. a.) | Taschenbuch | 184 S. | Englisch | 2011 | LAP LAMBERT Academic Publishing | EAN 9783845407975 | Verantwortliche Person für die EU: BoD - Books on Demand, In de Tarpen 42, 22848 Norderstedt, info[at]bod[dot]de | Anbieter: preigu.
Idioma: Inglés
Publicado por LAP LAMBERT Academic Publishing, 2011
ISBN 10: 3845407972 ISBN 13: 9783845407975
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Idioma: Inglés
Publicado por LAP LAMBERT Academic Publishing Jul 2011, 2011
ISBN 10: 3845407972 ISBN 13: 9783845407975
Librería: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Alemania
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Añadir al carritoTaschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -An seismic classification system was designed for the recognition of different vehicle categories: wheeled and tracked vehicle. The focus of this research was to study the usability of seismic features for distinction between these classes in traffic scenarios which include low and high vehicle s velocity and a combined traffic situation.classification system can be extended in a way that extracted features are utilized as characteristic fingerprints, which affords tracking of vehicles over multiple sensor nodes. 184 pp. Englisch.
Idioma: Inglés
Publicado por VDM Verlag Dr. Mueller Aktiengesellschaft & Co. KG, 2011
ISBN 10: 3845407972 ISBN 13: 9783845407975
Librería: Majestic Books, Hounslow, Reino Unido
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Añadir al carritoCondición: New. Print on Demand pp. 184 2:B&W 6 x 9 in or 229 x 152 mm Perfect Bound on Creme w/Gloss Lam.
Idioma: Inglés
Publicado por VDM Verlag Dr. Mueller Aktiengesellschaft & Co. KG, 2011
ISBN 10: 3845407972 ISBN 13: 9783845407975
Librería: Biblios, Frankfurt am main, HESSE, Alemania
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Añadir al carritoCondición: New. PRINT ON DEMAND pp. 184.
Idioma: Inglés
Publicado por LAP LAMBERT Academic Publishing, 2011
ISBN 10: 3845407972 ISBN 13: 9783845407975
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Añadir al carritoCondición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Singh BhopendraMr. Bhopendra Singh, Mr. Navdeep Sharma and Mr. Ashutosh Gupta are having rich experience in industry & academia in the field of signal & Image processing based applications. Currently they are associated with Amity Sc.
Idioma: Inglés
Publicado por LAP LAMBERT Academic Publishing Jul 2011, 2011
ISBN 10: 3845407972 ISBN 13: 9783845407975
Librería: buchversandmimpf2000, Emtmannsberg, BAYE, Alemania
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Añadir al carritoTaschenbuch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -An seismic classification system was designed for the recognition of different vehicle categories: wheeled and tracked vehicle. The focus of this research was to study the usability of seismic features for distinction between these classes in traffic scenarios which include low and high vehicle¿s velocity and a combined traffic situation.classification system can be extended in a way that extracted features are utilized as characteristic fingerprints, which affords tracking of vehicles over multiple sensor nodes.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 184 pp. Englisch.
Idioma: Inglés
Publicado por LAP LAMBERT Academic Publishing, 2011
ISBN 10: 3845407972 ISBN 13: 9783845407975
Librería: AHA-BUCH GmbH, Einbeck, Alemania
EUR 68,00
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Añadir al carritoTaschenbuch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - An seismic classification system was designed for the recognition of different vehicle categories: wheeled and tracked vehicle. The focus of this research was to study the usability of seismic features for distinction between these classes in traffic scenarios which include low and high vehicle s velocity and a combined traffic situation.classification system can be extended in a way that extracted features are utilized as characteristic fingerprints, which affords tracking of vehicles over multiple sensor nodes.