Jirari mohammed (4 risultati)
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Da: Revaluation Books, Exeter, Regno UnitoRevaluation Books
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 116,44
EUR 11,71 spedizioneSpedito da Regno Unito a U.S.A.Quantità: 1 disponibili
Paperback. Condizione: Brand New. 144 pages. 8.66x5.91x0.33 inches. In Stock.
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Da: Mispah books, Redhill, SURRE, Regno UnitoMispah books
Contatta il venditoreVenditore con 4 stelleCondizione: Nuovo
EUR 196,53
EUR 29,27 spedizioneSpedito da Regno Unito a U.S.A.Quantità: 1 disponibili
paperback. Condizione: New. NEW. SHIPS FROM MULTIPLE LOCATIONS. book.
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- Print on Demand
Da: moluna, Greven, Germaniamoluna
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EUR 46,32
EUR 48,99 spedizioneSpedito da Germania a U.S.A.Quantità: Più di 20 disponibili
Kartoniert / Broschiert. Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Jirari MohammedMohammed Jirari has received a B.S. in Computer Science with a nminor in Mathematics from Edinboro University of Pennsylvania, a nM.S. in Computer Science from L…amar University and a Ph.D. in nComputer Science from Ken.
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Da: AHA-BUCH GmbH, Einbeck, GermaniaAHA-BUCH GmbH
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 59,71
EUR 61,16 spedizioneSpedito da Germania a U.S.A.Quantità: 2 disponibili
Taschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - An intelligent CAD can be very helpful in detecting masses in the breast earlier and faster than typical screening programs. Two such systems are presented, First a system based on Radial Basis neural networks coupled with feature extra…ction techniques for detecting masses in mammograms. Suspicious regions are identified following a run of the trained neural network. Co-occurrence matrices are constructed at different distances for each mammogram. Statistical features are used to train and test the Radial Basis neural network. The second system presented was developed based on linear subtraction and feature extraction techniques to identify asymmetries between left and right breast mammograms. This system is based on the idea that a deviation from the normal architectural symmetry of the right and left breasts could indicate a cancerous mass. The results show that both systems could be helpful to the radiologist by serving as a second reader in mammography screening.
