An Approach for Device localization using audio fingerprinting based: on Hierarchical Cluster Analysis - Softcover
Synopsis
Audio fingerprinting is defined as a condensed digital summary to establish the equality or similarity of two audio objects. By comparing the fingerprinting of a query fragment of a few seconds with those stored in a fingerprinting database, the system returns matching results and related metadata. Besides this query-by-example application, this technology can also be used to monitor broadcast and detect copyrighted material. Audio fingerprinting is best known for its ability to link unlabeled audio to corresponding meta-data (e.g. artist and song name), regardless of the audio format. Audio fingerprinting or content-based audio identification (CBID) systems extract a perceptual digest of a piece of audio content, i.e. a fingerprint and store it in a database. When presented with unlabeled audio, its fingerprint is calculated and matched against those stored in the database. For the reader new to analysis of data a very short introduction is now provided on hierarchical clustering.
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About the Author
Mr. M. Muni Sankar received his M.Tech degree in Digital Electronics and communication systems from JNTU, Anantapur, India in 2012. He is currently working as an Assistant Professor in the Department of ECE, SoET, SPMVV, Tirupati, India. Muni Sankar also published couples of research articles and journals in international repute.
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An Approach for Device localization using audio fingerprinting based
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LAP LAMBERT Academic Publishing Jan 2017, 2017
ISBN 10: 3330033037
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Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Audio fingerprinting is defined as a condensed digital summary to establish the equality or similarity of two audio objects. By comparing the fingerprinting of a query fragment of a few seconds with those stored in a fingerprinting database, the system returns matching results and related metadata. Besides this query-by-example application, this technology can also be used to monitor broadcast and detect copyrighted material. Audio fingerprinting is best known for its ability to link unlabeled audio to corresponding meta-data (e.g. artist and song name), regardless of the audio format. Audio fingerprinting or content-based audio identification (CBID) systems extract a perceptual digest of a piece of audio content, i.e. a fingerprint and store it in a database. When presented with unlabeled audio, its fingerprint is calculated and matched against those stored in the database. For the reader new to analysis of data a very short introduction is now provided on hierarchical clustering. 64 pp. Englisch. Seller Inventory # 9783330033030
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An Approach for Device localization using audio fingerprinting based: on Hierarchical Cluster Analysis
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An Approach for Device localization using audio fingerprinting based
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Kartoniert / Broschiert. Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Matam Muni SankarMr. M. Muni Sankar received his M.Tech degree in Digital Electronics and communication systems from JNTU, Anantapur, India in 2012. He is currently working as an Assistant Professor in the Department of ECE, SoET, . Seller Inventory # 159137577
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An Approach for Device localization using audio fingerprinting based
Published by
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ISBN 10: 3330033037
ISBN 13: 9783330033030
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Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Audio fingerprinting is defined as a condensed digital summary to establish the equality or similarity of two audio objects. By comparing the fingerprinting of a query fragment of a few seconds with those stored in a fingerprinting database, the system returns matching results and related metadata. Besides this query-by-example application, this technology can also be used to monitor broadcast and detect copyrighted material. Audio fingerprinting is best known for its ability to link unlabeled audio to corresponding meta-data (e.g. artist and song name), regardless of the audio format. Audio fingerprinting or content-based audio identification (CBID) systems extract a perceptual digest of a piece of audio content, i.e. a fingerprint and store it in a database. When presented with unlabeled audio, its fingerprint is calculated and matched against those stored in the database. For the reader new to analysis of data a very short introduction is now provided on hierarchical clustering.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 64 pp. Englisch. Seller Inventory # 9783330033030
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An Approach for Device localization using audio fingerprinting based : on Hierarchical Cluster Analysis
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Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Audio fingerprinting is defined as a condensed digital summary to establish the equality or similarity of two audio objects. By comparing the fingerprinting of a query fragment of a few seconds with those stored in a fingerprinting database, the system returns matching results and related metadata. Besides this query-by-example application, this technology can also be used to monitor broadcast and detect copyrighted material. Audio fingerprinting is best known for its ability to link unlabeled audio to corresponding meta-data (e.g. artist and song name), regardless of the audio format. Audio fingerprinting or content-based audio identification (CBID) systems extract a perceptual digest of a piece of audio content, i.e. a fingerprint and store it in a database. When presented with unlabeled audio, its fingerprint is calculated and matched against those stored in the database. For the reader new to analysis of data a very short introduction is now provided on hierarchical clustering. Seller Inventory # 9783330033030
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An Approach for Device localization using audio fingerprinting based | on Hierarchical Cluster Analysis
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ISBN 10: 3330033037
ISBN 13: 9783330033030
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Taschenbuch. Condition: Neu. An Approach for Device localization using audio fingerprinting based | on Hierarchical Cluster Analysis | Muni Sankar Matam (u. a.) | Taschenbuch | 64 S. | Englisch | 2017 | LAP LAMBERT Academic Publishing | EAN 9783330033030 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu. Seller Inventory # 108383505
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