Sinossi
Each image in a Content Based Image Retrieval (CBIR) system is represented by its features such as colour, texture and shape. These three groups of features are stored in the feature vector. Therefore, each image managed by the CBIR system is associated with one or more feature vectors. This book presents an improved approach to select significant features from the huge image feature vector. The concept behind this research is that it is possible to extract image feature relational patterns in an image feature vector database. After which, these relational patterns are used to generate rules and improve the retrieval results for a CBIR system. In addition, this research proposes a CBIR system utilising the Rough Set instead of deterministic and crisp methods. In this research, Rough Set rules are evaluated with noisy images. Also, in order to have a more accurate classifier in the CBIR system, the classifier is proposed to be based on the Rough Set and Support Vector Machine (SVM) in this research.
Le informazioni nella sezione "Riassunto" possono far riferimento a edizioni diverse di questo titolo.
Informazioni sull?autore
Dr. Maryam Shahabi has a PhD degree in Information Technology and Master Degree in Artificial Intelligence. She worked and taught in the Information Technology environment for the past seven years in both industry and in academic environments. Her research interests are Image retrieval, soft computing, Artificial intelligence and machine learning.
Le informazioni nella sezione "Su questo libro" possono far riferimento a edizioni diverse di questo titolo.
Risultati della ricerca per OCEAN SOUNDS SENSUOUS MASSAGE ORM 61312
Immagini fornite dal venditore
Image Retrieval System and Rough Set Theory
Editore:
LAP LAMBERT Academic Publishing Nov 2016, 2016
ISBN 10: 3330007370
ISBN 13: 9783330007376
Nuovo
Taschenbuch
Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germania
Valutazione del venditore 5 su 5 stelle
Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Each image in a Content Based Image Retrieval (CBIR) system is represented by its features such as colour, texture and shape. These three groups of features are stored in the feature vector. Therefore, each image managed by the CBIR system is associated with one or more feature vectors. This book presents an improved approach to select significant features from the huge image feature vector. The concept behind this research is that it is possible to extract image feature relational patterns in an image feature vector database. After which, these relational patterns are used to generate rules and improve the retrieval results for a CBIR system. In addition, this research proposes a CBIR system utilising the Rough Set instead of deterministic and crisp methods. In this research, Rough Set rules are evaluated with noisy images. Also, in order to have a more accurate classifier in the CBIR system, the classifier is proposed to be based on the Rough Set and Support Vector Machine (SVM) in this research. 180 pp. Englisch. Codice articolo 9783330007376
Compra nuovo
EUR 64,90
Spedizione EUR 23,00
Spedito da Germania a U.S.A.
Spedito da Germania a U.S.A.
Quantità: 2 disponibili
Immagini fornite dal venditore
Image Retrieval System and Rough Set Theory
Editore:
LAP LAMBERT Academic Publishing, 2016
ISBN 10: 3330007370
ISBN 13: 9783330007376
Nuovo
Brossura
Da: moluna, Greven, Germania
Valutazione del venditore 5 su 5 stelle
Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Shahabi Lotfabadi MaryamDr. Maryam Shahabi has a PhD degree in Information Technology and Master Degree in Artificial Intelligence. She worked and taught in the Information Technology environment for the past seven years in both indu. Codice articolo 151233822
Compra nuovo
EUR 52,90
Spedizione EUR 48,99
Spedito da Germania a U.S.A.
Spedito da Germania a U.S.A.
Quantità: Più di 20 disponibili
Foto dell'editore
Image Retrieval System and Rough Set Theory
Editore:
LAP LAMBERT Academic Publishing, 2016
ISBN 10: 3330007370
ISBN 13: 9783330007376
Nuovo
Paperback
Da: Revaluation Books, Exeter, Regno Unito
Valutazione del venditore 5 su 5 stelle
Paperback. Condizione: Brand New. 01 edition. 180 pages. 8.66x5.91x0.41 inches. In Stock. Codice articolo 3330007370
Compra nuovo
EUR 104,29
Spedizione EUR 11,58
Spedito da Regno Unito a U.S.A.
Spedito da Regno Unito a U.S.A.
Quantità: 1 disponibili
Immagini fornite dal venditore
Image Retrieval System and Rough Set Theory
Editore:
LAP LAMBERT Academic Publishing Nov 2016, 2016
ISBN 10: 3330007370
ISBN 13: 9783330007376
Nuovo
Taschenbuch
Da: buchversandmimpf2000, Emtmannsberg, BAYE, Germania
Valutazione del venditore 5 su 5 stelle
Taschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Each image in a Content Based Image Retrieval (CBIR) system is represented by its features such as colour, texture and shape. These three groups of features are stored in the feature vector. Therefore, each image managed by the CBIR system is associated with one or more feature vectors. This book presents an improved approach to select significant features from the huge image feature vector. The concept behind this research is that it is possible to extract image feature relational patterns in an image feature vector database. After which, these relational patterns are used to generate rules and improve the retrieval results for a CBIR system. In addition, this research proposes a CBIR system utilising the Rough Set instead of deterministic and crisp methods. In this research, Rough Set rules are evaluated with noisy images. Also, in order to have a more accurate classifier in the CBIR system, the classifier is proposed to be based on the Rough Set and Support Vector Machine (SVM) in this research.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 180 pp. Englisch. Codice articolo 9783330007376
Compra nuovo
EUR 64,90
Spedizione EUR 60,00
Spedito da Germania a U.S.A.
Spedito da Germania a U.S.A.
Quantità: 1 disponibili
Immagini fornite dal venditore
Image Retrieval System and Rough Set Theory
Editore:
LAP LAMBERT Academic Publishing, 2016
ISBN 10: 3330007370
ISBN 13: 9783330007376
Nuovo
Taschenbuch
Da: preigu, Osnabrück, Germania
Valutazione del venditore 5 su 5 stelle
Taschenbuch. Condizione: Neu. Image Retrieval System and Rough Set Theory | Maryam Shahabi Lotfabadi | Taschenbuch | 180 S. | Englisch | 2016 | LAP LAMBERT Academic Publishing | EAN 9783330007376 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu. Codice articolo 107977538
Compra nuovo
EUR 55,55
Spedizione EUR 70,00
Spedito da Germania a U.S.A.
Spedito da Germania a U.S.A.
Quantità: 5 disponibili
Immagini fornite dal venditore
Image Retrieval System and Rough Set Theory
Editore:
LAP LAMBERT Academic Publishing, 2016
ISBN 10: 3330007370
ISBN 13: 9783330007376
Nuovo
Taschenbuch
Da: AHA-BUCH GmbH, Einbeck, Germania
Valutazione del venditore 5 su 5 stelle
Taschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Each image in a Content Based Image Retrieval (CBIR) system is represented by its features such as colour, texture and shape. These three groups of features are stored in the feature vector. Therefore, each image managed by the CBIR system is associated with one or more feature vectors. This book presents an improved approach to select significant features from the huge image feature vector. The concept behind this research is that it is possible to extract image feature relational patterns in an image feature vector database. After which, these relational patterns are used to generate rules and improve the retrieval results for a CBIR system. In addition, this research proposes a CBIR system utilising the Rough Set instead of deterministic and crisp methods. In this research, Rough Set rules are evaluated with noisy images. Also, in order to have a more accurate classifier in the CBIR system, the classifier is proposed to be based on the Rough Set and Support Vector Machine (SVM) in this research. Codice articolo 9783330007376
Compra nuovo
EUR 64,90
Spedizione EUR 61,43
Spedito da Germania a U.S.A.
Spedito da Germania a U.S.A.
Quantità: 1 disponibili
Foto dell'editore
Image Retrieval System and Rough Set Theory
Editore:
LAP LAMBERT Academic Publishing, 2016
ISBN 10: 3330007370
ISBN 13: 9783330007376
Nuovo
paperback
Da: Mispah books, Redhill, SURRE, Regno Unito
Valutazione del venditore 4 su 5 stelle
paperback. Condizione: New. NEW. SHIPS FROM MULTIPLE LOCATIONS. book. Codice articolo ERICA82933300073706
Compra nuovo
EUR 181,25
Spedizione EUR 28,94
Spedito da Regno Unito a U.S.A.
Spedito da Regno Unito a U.S.A.
Quantità: 1 disponibili