Prashant Verma

After pondering about it for some time, I realized that the main difference is this: in the normal convolution, we are transforming the image 256 times. And every transformation uses up 5x5x3x8x8=4800 multiplications. In the separable convolution, we only really transform the image once — in the depthwise convolution. Then, we take the transformed image and simply elongate it to 256 channels. Without having to transform the image over and over again, we can save up on computational power.

vation function also has a significant impact on the speed of learning, which is one of the main criteria for their selection…ement allows for greater flexibility and creation of complex functions during the learning process. The activation function also has a significant impact on the speed of learning, which is one of the main criteria for their selection. Figure 6 shows some of the commonly used activation functions. Currently, the most popular one for …

Cross-entropy is always larger than entropy and it will be same as entropy only when pi=qi. You could digest the last sentence after seeing really nice plot given by desmos.com