Illustrated: 10 CNN Architectures

If you're thinking about ResNets, yes, they are related. ResNeXt-50 has 25M parameters (ResNet-50 has 25.5M). What's different about ResNeXts is the adding of parallel towers/branches/paths within each module, as seen above indicated by'total 32 towers.' Recall that in a convolution, the value of a pixel is a linear combination of the weights in a filter and the current sliding window. The authors proposed that instead of this linear combination, let's have a mini neural network with 1 hidden layer.