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Date:06.06.2017, 20:55 This amount still seems manageable, but clearly this fully-connected structure does not scale to larger images. For example, an image of more respectable size, e.g. 200x200x3, would lead to neurons that have,000 weights. A ConvNet is made up of Layers. Every Layer has a simple API: It transforms an input 3D volume to an output 3D volume with some differentiable function that may or may not have parameters. Table of Contents: Architecture Overview ConvNet Layers Convolutional Layer Pooling Layer. Normalization Layer Fully-Connected Layer Converting Fully-Connected Layers to Convolutional Layers. ConvNet Architectures Layer Patterns Layer Sizing Patterns Case Studies (LeNet / AlexNet / ZFNet / GoogLeNet / VGGN et) Computational Considerations Additional References.
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