WebOct 8, 2024 · The architecture of Vgg 16. The Kernel size is 3x3 and the pool size is 2x2 for all the layers. The input to the Vgg 16 model is 224x224x3 pixels images. then we have two convolution layers with ... WebAlexNet Architecture. The input dimensions of the network are (256 × 256 × 3), meaning that the input to AlexNet is an RGB (3 channels) image of (256 × 256) pixels. There are more than 60 million parameters and 650,000 neurons involved in the architecture. To reduce overfitting during the training process, the network uses dropout layers.
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Inception
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