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Content Based Document Image by H T Chandrakala (8 results)
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Content Based Document Image Retrieval
Language: English
Published by LAP LAMBERT Academic Publishing, 2020
ISBN 10: 6202796278 ISBN 13: 9786202796279
Condition: New.
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Content Based Document Image Retrieval
Language: English
Published by LAP LAMBERT Academic Publishing, 2020
ISBN 10: 6202796278 ISBN 13: 9786202796279
Taschenbuch. Condition: Neu. Content Based Document Image Retrieval | Chandrakala H. T. | Taschenbuch | Englisch | 2020 | LAP LAMBERT Academic Publishing | EAN 9786202796279 | Verantwortliche Person für die EU: LAP Lambert Academic Publishing, Brivibas Gatve 197, 1039 RIGA, LETTLAND, customerservice[at]vdm-vsg[dot]de | Anbieter: preigu.
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Content Based Document Image Retrieval
Language: English
Published by LAP LAMBERT Academic Publishing Aug 2020, 2020
ISBN 10: 6202796278 ISBN 13: 9786202796279
Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germany
Seller rating 5 out of 5 stars
Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book presents an efficient Content Based Document Image Retrieval system for a Kannada document image collection. A recognition-free approach is followed because recognition based approach is inefficient in terms of performance. The data is preprocessed and segmented for faster matching and retrieval. Correlation Coefficient technique is used to search in large collection of document images. Performance evaluation using different Kannada document datasets to show the effectiveness of the approach. 88 pp. Englisch.
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Content Based Document Image Retrieval
Language: English
Published by LAP LAMBERT Academic Publishing, 2020
ISBN 10: 6202796278 ISBN 13: 9786202796279
Condition: New. Print on Demand.
-
Content Based Document Image Retrieval
Language: English
Published by LAP LAMBERT Academic Publishing, 2020
ISBN 10: 6202796278 ISBN 13: 9786202796279
Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: H.T. ChandrakalaDr Chandrakala H T received PhD from the Department of Computer Science and Engineering, Visveswaraya Technological University, Belgaum, India in 2019. Her present research interests are image enhancement, segmentatio.
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Content Based Document Image Retrieval
Language: English
Published by LAP LAMBERT Academic Publishing, 2020
ISBN 10: 6202796278 ISBN 13: 9786202796279
Condition: New. PRINT ON DEMAND.
-
Content Based Document Image Retrieval
Language: English
Published by LAP LAMBERT Academic Publishing Aug 2020, 2020
ISBN 10: 6202796278 ISBN 13: 9786202796279
Seller: buchversandmimpf2000, Emtmannsberg, BAYE, Germany
Seller rating 5 out of 5 stars
Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -This book presents an efficient Content Based Document Image Retrieval system for a Kannada document image collection. A recognition-free approach is followed because recognition based approach is inefficient in terms of performance. The data is preprocessed and segmented for faster matching and retrieval. Correlation Coefficient technique is used to search in large collection of document images. Performance evaluation using different Kannada document datasets to show the effectiveness of the approach.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 88 pp. Englisch.
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Content Based Document Image Retrieval
Language: English
Published by LAP LAMBERT Academic Publishing, 2020
ISBN 10: 6202796278 ISBN 13: 9786202796279
Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - This book presents an efficient Content Based Document Image Retrieval system for a Kannada document image collection. A recognition-free approach is followed because recognition based approach is inefficient in terms of performance. The data is preprocessed and segmented for faster matching and retrieval. Correlation Coefficient technique is used to search in large collection of document images. Performance evaluation using different Kannada document datasets to show the effectiveness of the approach.
