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What is Depthwise Separable Convolutions about?

Depthwise Separable Convolution (DSC) is an efficient 2D convolution technique that reduces the number of FLOPs and learnable parameters, leading to lower processing power and faster inference at a slight accuracy cost. It splits the convolution into two parts: depthwise convolution and pointwise convolution, significantly decreasing the number of learnable parameters from 204K in standard convolution to 9,792 in DSC. This method results in reduced computational resources and memory usage, enhancing inferen

Author

Rajesh

Language

EN