What does 1x1 convolution mean in a neural network?
1x1 conv creates channel-wise dependencies with a negligible cost. This is especially exploited in depthwise-separable convolutions. Nobody said anything about this but I'm writing this as a …
What is the difference between Conv1D and Conv2D?
Jul 31, 2017 · I will be using a Pytorch perspective, however, the logic remains the same. When using Conv1d (), we have to keep in mind that we are most likely going to work with 2 …
neural networks - Difference between strided and non-strided ...
Aug 6, 2018 · conv = conv_2d (strides=) I want to know in what sense a non-strided convolution differs from a strided convolution. I know how convolutions with strides work but I am not …
How is RELU used on convolutional layer - Cross Validated
Apr 25, 2019 · The answer that you might be looking for is that ReLU is applied element-wise (to each element individually) to the learned parameters of the conv layer ("feature maps").
Convolutional Layers: To pad or not to pad? - Cross Validated
If the CONV layers were to not zero-pad the inputs and only perform valid convolutions, then the size of the volumes would reduce by a small amount after each CONV, and the information at …
In CNN, are upsampling and transpose convolution the same?
Sep 24, 2019 · It may depend on the package you are using. In keras they are different. Upsampling is defined here Provided you use tensorflow backend, what actually happens is …
What are the advantages of FC layers over Conv layers?
Sep 23, 2020 · I am trying to think of scenarios where a fully connected (FC) layer is a better choice than a convolution layer. In terms of time complexity, are they the same? I know that …
Difference between Conv and FC layers? - Cross Validated
Nov 9, 2017 · What is the difference between conv layers and FC layers? Why cannot I use conv layers instead of FC layers?
neural networks - How does convolution work? - Cross Validated
Aug 18, 2020 · Replace the second FC layer with a CONV layer that uses filter size F=1, giving output volume [1x1x4096] Replace the last FC layer similarly, with F=1, giving final output …
How to calculate the Transposed Convolution? - Cross Validated
Sep 3, 2022 · Studying for my finals in Deep learning. I'm trying to solve the following question: Calculate the Transposed Convolution of input $A$ with kernel $K$: $$ A=\begin ...