# Questions tagged [convolution]

Convolution is a function-valued operation on two functions $f$ and $g$: $\int _{-\infty }^{\infty }f(\tau )g(t-\tau )d\tau$. Often used for obtaining the density of a sum of independent random variables. This tag should also be used for the inverse operation of deconvolution. DO NOT use this tag for convolutional neural networks.

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### 3D convolutions and jitter

I want to process a sequence of cropped and aligned face images from a video with a neural network. I am considering a use of 3D convolutions in order to capture the spatiotemporal dependency. However,...
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### Why does MobileNet Architecture start with a Standard Convolution?

I am trying to understand the design choices behind the MobileNet architecture. (pdf available on the right). The authors use Depthwise Separable Convolutions as a replacement for Classical ...
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### How to count the parameters in a convolution layer?

I'm preparing for an exam in Computer Vision. I came across with the following question from one of the exams: What is the number of parameters of a convolution layer in a neural network, when the ...
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### How to obtain the density of a sum of independent discrete random variables?

Let's $X_1, X_2, ..., X_n$, $n=1,2,...$ are independent discrete random variables. It is necessary to find the distribution law of the their sum: $p(k) =P(X_1 + X_2 + ... + X_n = k), k=0, 1, 2, ...$ ...
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### What is the best way to feed IMU data to CNN?

I took the Introduction to Embedded Machine Learning course, which is provided by Shawn Hymel, on Coursera. While talking about sensor fusion, he made the following statement for the following diagram:...
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