Applied Intelligence and Informatics by Unknown
Author:Unknown
Language: eng
Format: epub
ISBN: 9783030822699
Publisher: Springer International Publishing
1.
RELU and batch normalization with dense (1024) defines the fully connected layer where dropout is executed for the last time. This time 50% of the node is being dropped during training.
2.
Finally, sigmoid function is used as classifier to return the predicted probabilities for each class label.
In Fig. 5 the whole schematic diagram of our network architecture has been provided.
4 Experimental Setup
Our system has been implemented using python programming language. Matplotlib, keras, numpy libraries has been used for system implementation. Keras provides some built in functions such as activation functions, optimizers, layers etc. Tensorflow has also been used as the system backend. In Table 1, the experimental tools used in this system implementation has been showed.
Fig. 5.A full schematic diagram of network architecture
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