Depthwise Separable Convolution

An efficient neural network operation that factorizes a standard convolution into two simpler operations: a depthwise convolution and a pointwise convolution. This reduces computational cost by 8-9x while maintaining similar accuracy. Used extensively in MobileNet and other efficient architectures designed for edge deployment.