Idioma: Inglés
Publicado por LAP LAMBERT Academic Publishing, 2020
ISBN 10: 6200472548 ISBN 13: 9786200472540
Librería: Books Puddle, New York, NY, Estados Unidos de America
EUR 64,71
Cantidad disponible: 4 disponibles
Añadir al carritoCondición: New.
Idioma: Inglés
Publicado por LAP LAMBERT Academic Publishing, 2020
ISBN 10: 6200472548 ISBN 13: 9786200472540
Librería: Revaluation Books, Exeter, Reino Unido
EUR 65,43
Cantidad disponible: 1 disponibles
Añadir al carritoPaperback. Condición: Brand New. 88 pages. 8.66x5.91x0.20 inches. In Stock.
Idioma: Inglés
Publicado por LAP LAMBERT Academic Publishing, 2020
ISBN 10: 6200472548 ISBN 13: 9786200472540
Librería: moluna, Greven, Alemania
EUR 34,25
Cantidad disponible: Más de 20 disponibles
Añadir al carritoCondición: New.
Idioma: Inglés
Publicado por LAP LAMBERT Academic Publishing Feb 2020, 2020
ISBN 10: 6200472548 ISBN 13: 9786200472540
Librería: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Alemania
EUR 39,90
Cantidad disponible: 2 disponibles
Añadir al carritoTaschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -In this book, comparison on performance of artificial neural network and transfer learning is made for classification of breast cancer into malignant and benign. First artificial neural network topology is design using three hidden layers used for feature extraction and after that softmax layer is used for prediction of cancer as malignant and benign. After that deep convolutional neural network transfer learning model is used where VGG19 which is pretrained model is used for feature extraction and after that dense layers are there which are used for final prediction. So the proposed model with transfer learning outperforms the artificial neural network model with overall accuracy of 98.4% and also beat previous convolutional neural network model. In future we can use other transfer learning models like Resnet50, InceptionV3 to increase further accuracy of the model. 88 pp. Englisch.
Idioma: Inglés
Publicado por LAP LAMBERT Academic Publishing, 2020
ISBN 10: 6200472548 ISBN 13: 9786200472540
Librería: Majestic Books, Hounslow, Reino Unido
EUR 63,32
Cantidad disponible: 4 disponibles
Añadir al carritoCondición: New. Print on Demand.
Idioma: Inglés
Publicado por LAP LAMBERT Academic Publishing, 2020
ISBN 10: 6200472548 ISBN 13: 9786200472540
Librería: Biblios, Frankfurt am main, HESSE, Alemania
EUR 64,00
Cantidad disponible: 4 disponibles
Añadir al carritoCondición: New. PRINT ON DEMAND.
Idioma: Inglés
Publicado por LAP LAMBERT Academic Publishing Feb 2020, 2020
ISBN 10: 6200472548 ISBN 13: 9786200472540
Librería: buchversandmimpf2000, Emtmannsberg, BAYE, Alemania
EUR 39,90
Cantidad disponible: 1 disponibles
Añadir al carritoTaschenbuch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -In this book, comparison on performance of artificial neural network and transfer learning is made for classification of breast cancer into malignant and benign. First artificial neural network topology is design using three hidden layers used for feature extraction and after that softmax layer is used for prediction of cancer as malignant and benign. After that deep convolutional neural network transfer learning model is used where VGG19 which is pretrained model is used for feature extraction and after that dense layers are there which are used for final prediction. So the proposed model with transfer learning outperforms the artificial neural network model with overall accuracy of 98.4% and also beat previous convolutional neural network model. In future we can use other transfer learning models like Resnet50, InceptionV3 to increase further accuracy of the model.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 88 pp. Englisch.
Idioma: Inglés
Publicado por LAP LAMBERT Academic Publishing, 2020
ISBN 10: 6200472548 ISBN 13: 9786200472540
Librería: AHA-BUCH GmbH, Einbeck, Alemania
EUR 40,89
Cantidad disponible: 1 disponibles
Añadir al carritoTaschenbuch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - In this book, comparison on performance of artificial neural network and transfer learning is made for classification of breast cancer into malignant and benign. First artificial neural network topology is design using three hidden layers used for feature extraction and after that softmax layer is used for prediction of cancer as malignant and benign. After that deep convolutional neural network transfer learning model is used where VGG19 which is pretrained model is used for feature extraction and after that dense layers are there which are used for final prediction. So the proposed model with transfer learning outperforms the artificial neural network model with overall accuracy of 98.4% and also beat previous convolutional neural network model. In future we can use other transfer learning models like Resnet50, InceptionV3 to increase further accuracy of the model.