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 do bottleneck architectures work in neural networks?
We define a bottleneck architecture as the type found in the ResNet paper where [two 3x3 conv layers] are replaced by [one 1x1 conv, one 3x3 conv, and another 1x1 conv layer]. I …
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?
deep learning - What is the definition of a "feature map" (aka ...
Jul 16, 2017 · Typical-looking activations on the first CONV layer (left), and the 5th CONV layer (right) of a trained AlexNet looking at a picture of a cat. Every box shows an activation map …
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 …
How to obtain the last convolutional layer of a model in …
Oct 21, 2023 · I'm not sure, because the last convolutional layer can vary in each model. And my main concern is regarding which is the last convolutional layer of the efficient net b0.
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 ...
Understanding the output shape of the following YOLO network
Dec 24, 2022 · Below you can see a convolutional network with 24 convolutional layers. I am trying to understand the shape of the network. Given the input image with shape 448x448x3, …