0
$\begingroup$

What does the number 16 (no. of outputs) represent in this Convo layer?

 layers.Conv2D(16, 3, padding='same', activation='relu'),
$\endgroup$
1
  • $\begingroup$ Hi @ShushilKgadka, welcome to the site. Here you have some context on the concept of "channels" in a convolutional layer. $\endgroup$
    – noe
    Jun 17 at 22:27

1 Answer 1

0
$\begingroup$

It means that you have 16 filters of 3x3 kernels. If you check the number of trainable parameters, you have : 16 filters x 9 parameters per kernel x 3 channels (for RGB images) + 16 biaises (one per filter) = 448 trainable parameters

$\endgroup$
2
  • $\begingroup$ So the software knows that both dimensions are $3$ pixels if you only specify one number? I feel like I’ve always specified both dimensions. $\endgroup$
    – Dave
    Aug 18, 2022 at 21:35
  • $\begingroup$ If you mean the size of the kernel yes , it does understand its a 3 X 3 kernel in case of 1 channel image and 3 x 3 x n in a n channel image. $\endgroup$ Aug 19, 2022 at 1:18

Your Answer

By clicking “Post Your Answer”, you agree to our terms of service and acknowledge that you have read and understand our privacy policy and code of conduct.

Not the answer you're looking for? Browse other questions tagged or ask your own question.