# Questions tagged [convolution]

For questions related to the convolution operation in mathematics, convolutional neural networks, image processing and computer vision.

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### What are the benefits of using multiple convolutions, as opposed to one, before the pooling layer in a U-Net?

I have seen U-Nets that use a single convolution before the pooling operator and some that use two or more. My question is, what is better? Or what are the benefits of using more or less convolutions?
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### What happens in tensorflow/pytorch under the hood when doing a convolution2d() with x filters when num input feature maps/channels > x? [duplicate]

I was wondering about what happens in tensorflow/pytorch under the hood when doing a convolution2d() with x filters when num input feature maps/channels > x? e.g. my input shape with 129 feature ...
24 views

### Implement 4D convolution as matrix-matrix multiplication - paper is confusing!

I am confused by this paper https://arxiv.org/pdf/1410.0759.pdf which displays on page 4 how to model a 3D convolution (input has more than 1 channel and filter has more than one output). In this ...
13 views

### How are CNN kernels trained when using FFT for convolutions?

CNNs (convolutional neural networks) are adept at processing images, as their construction is based on the biological neural networks found in the human eye. "Kernels", sometimes called &...
16 views

### How do I compute the convolution of two kernels of the same size in practice?

Suppose I have a 256-by-256 input matrix called $X$ and two 3-by-3 kernels called $K_1$ and $K_2$. By the associativity of convolution \begin{equation} (X \star K_1) \star K_2 = X \star (K_1 \star K_2)...
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### Is down-sampling the only purpose of using stride?

Stride is used in at least two operations: convolution and pooling. Both operations can be viewed as applying a kernel function on input using a kernel (filter). Stride determines the amount of "...
34 views

### Orthogonalizing Convolutional Layers with the Cayley Transform

I'm reading this paper: "Orthogonalizing Convolutional Layers with the Cayley Transform" regarding the orthogonalization of convolutional layers, i.e. enforcing learning of orthogonal ...
1 vote
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### What is a filter in the context of graph convolutional networks?

In Section 2.1 of the research paper titled Semi-Supervised Classification with Graph Convolutional Networks by Thomas N. Kipf et al., Spectral convolution on graphs defined as The multiplication of ...
139 views

### In this paper, if region $R_{2}$ moves in a sliding window manner, won't the saliency map have a smaller size than the original image?

In the paper Salient Region Detection and Segmentation, I have a question pertaining to section 3 on the convolution-like operation being performed. I had already asked a few questions about the paper ... 135 views

### How do I choose the hyper-parameters for a model to detect different guitar chords?

I need to build a hand detector that recognizes the chord played by a hand on a guitar. I read this article Static Hand Gesture Recognition using Convolutional Neural Network with Data Augmentation ...
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### Is it possible to apply 2D convolution to 1D data?

Suppose that I have a 1D dataset with 6 features. Can I apply a 2D convolutional neural net to this dataset?
1 vote
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139 views

### In CNNs, why do we sum the filter derivatives w.r.t the loss function to get the final gradient?

In a Convolutional Neural Network, unlike the fully connected layers, the same filter is used multiple times on the input while convolving - so during backpropagation, we get multiple derivatives for ...
1 vote