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.
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Vendeur : BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Allemagne
Taschenbuch. Etat : 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. N° de réf. du vendeur 9786200472540
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Vendeur : Majestic Books, Hounslow, Royaume-Uni
Etat : New. Print on Demand. N° de réf. du vendeur 401424623
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Vendeur : Books Puddle, New York, NY, Etats-Unis
Etat : New. N° de réf. du vendeur 26396033840
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Vendeur : Biblios, Frankfurt am main, HESSE, Allemagne
Etat : New. PRINT ON DEMAND. N° de réf. du vendeur 18396033850
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Vendeur : Revaluation Books, Exeter, Royaume-Uni
Paperback. Etat : Brand New. 88 pages. 8.66x5.91x0.20 inches. In Stock. N° de réf. du vendeur zk6200472548
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Vendeur : moluna, Greven, Allemagne
Etat : New. N° de réf. du vendeur 385891982
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Vendeur : buchversandmimpf2000, Emtmannsberg, BAYE, Allemagne
Taschenbuch. Etat : 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. N° de réf. du vendeur 9786200472540
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Vendeur : AHA-BUCH GmbH, Einbeck, Allemagne
Taschenbuch. Etat : 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. N° de réf. du vendeur 9786200472540
Quantité disponible : 1 disponible(s)