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 was going through the keras convolution docs and I have found two types of convultuion Conv1D and Conv2D. I did some web search and this is what I understands about …
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 …
In CNN, are upsampling and transpose convolution the same?
Sep 24, 2019 · Both the terms "upsampling" and "transpose convolution" are used when you are doing "deconvolution" (<-- not a good term, but let me use it here). Originally, I thought 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?
Pooling vs. stride for downsampling - Cross Validated
Jan 16, 2019 · Pooling and stride both can be used to downsample the image. Let's say we have an image of 4x4, like below and a filter of 2x2. Then how do we decide whether to use (2x2 …
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 …
Where should I place dropout layers in a neural network?
May 18, 2024 · I've updated the answer to clarify that in the work by Park et al., the dropout was applied after the RELU on each CONV layer. I do not believe they investigated the effect of …
How does applying a 1-by-1 convolution (bottleneck layer) …
Apr 17, 2020 · A 1-by-1 convolutional layer can (e.g.) be used to reduce the number of operations between two conv. layers. Example: applying a $5 \times 5 \times 32$ conv. with same …