August 2018
Intermediate to advanced
438 pages
12h 3m
English
Content preview from Hands-On Transfer Learning with Python
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AlexNet
In 2012, AlexNet significantly outperformed all the prior competitors and won the ILSVRC by reducing the top-5 error to 15.3%, compared to the runner-up with 26%. This work popularized the application of CNNs in computer vision. AlexNet has a very similar architecture to that of LeNet, but has more filters per layer and is deeper. Also, AlexNet introduces the use of stacked convolution, instead of always using alternative convolution pooling. A stack of small convolutions is better than one large receptive field of convolution layers, as this introduces more non-linearities and fewer parameters.
Suppose we have three 3 x 3 convolution layers on top of each other (with non-linearity or pooling layer in between). Here, each neuron on ...
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