August 2018
Intermediate to advanced
438 pages
12h 3m
English
Content preview from Hands-On Transfer Learning with Python
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ZFNet
The ILSVRC 2013 winner was a CNN from Matthew Zeiler and Rob Fergus. It became known as ZFNet. It improved on AlexNet by tweaking the architecture hyperparameters, in particular by expanding the size of the middle convolutional layers and making the stride and filter size on the first layer smaller, going from 11 x 11 stride 4 in AlexNet to 7 x 7 stride 2 in ZFNet. The intuition behind this was that a smaller filter size in the first convolution layer helps to retain a lot of the original pixel information. Also, AlexNet was trained on 15 million images, while ZFNet was trained on only 1.3 million images:
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