transition_block: Apply BatchNorm, ...
In dfalbel/densenet: Densely Connected Convolutional Networks in Keras
Description
... Relu 1x1, Conv2D, optional compression, dropout and
Maxpooling2D
Usage
1
2
transition_block(ip, nb_filter, compression = 1, dropout_rate = NULL,
weight_decay = 1e-04)
Arguments
ip
Input keras tensor
nb_filter
number of filters
compression
calculated as 1 - reduction. Reduces the number of
feature maps in the transition block.
dropout_rate
dropout rate
weight_decay
weight decay factor
dfalbel/densenet documentation built on May 31, 2019, 11:49 p.m.
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Description
... Relu 1x1, Conv2D, optional compression, dropout and Maxpooling2D
Usage
1 2 | transition_block(ip, nb_filter, compression = 1, dropout_rate = NULL,
weight_decay = 1e-04)
|
Arguments
ip |
Input keras tensor |
nb_filter |
number of filters |
compression |
calculated as 1 - reduction. Reduces the number of feature maps in the transition block. |
dropout_rate |
dropout rate |
weight_decay |
weight decay factor |
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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