Questions tagged [convolution]

For questions related to the convolution operation or convolutional layer (in the case of convolutional neural networks).

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6
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1answer
152 views

What are the benefits of using max-pooling in convolutional neural networks?

I am reading Francois Chollet's Deep learning with Python, and I came across a section about max-pooling that's really giving me trouble. I am unable to copy-paste the content, so I've included ...
6
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0answers
101 views

Why would you implement the position-wise feed-forward network of the transformer with convolution layers?

The Transformer model introduced in "Attention is all you need" by Vaswani et al. incorporates a so-called position-wise feed-forward network (FFN): In addition to attention sub-layers, each of the ...
4
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2answers
256 views

When should I use 3D convolution?

I am new to convolutional neural networks, and I am learning 3D convolution. What I could understand is that 2D convolution gives us relationships between low-level features in the X-Y dimension, ...
4
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1answer
46 views

Combining mean pooling and max pooling

Is it popular or effective to concatenate the results of mean-pooling and max-pooling? To get the invariance of the latter and the expressivity of the former.
4
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1answer
95 views

What is the difference between asymmetric and depthwise separable convolution?

I have recently discovered asymmetric convolution layers in deep learning architectures, a concept which seems very similar to depthwise separable convolutions. Are they really the same concept with ...
3
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2answers
71 views

Wouldn't convolutional neural network models work better without flattening the input in any stages?

The above model is what really helped me understand the implementation of convolutional neural networks, so based on that, I've got a tricky hypothesis that I want to find more about, since actually ...
3
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1answer
52 views

Is it useful to eliminate the less relevant filters from a trained CNN?

Imagine I have a tensorflow CNN model with good accuracy but maybe too many filters: Is there a way to determine which filters have more impact in output? I think it should be possible. At least, if ...
2
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1answer
19 views

Can I shuffle image channel data as a form of data augmentation?

If I want to augment my dataset, is shuffling or permuting the channels (RGB) of an image a sensible augmentation for training a CNN? IIRC, the way convolutions work is that a kernel operates over ...
2
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1answer
30 views

Is it possible to vectorise a CNN?

I am trying to write a CNN from scratch and am wondering if it possible to vectorise the convolution step. For example, if I had a dataset of 500 RGB images of size 32x32x3, and wanted the first conv ...
2
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2answers
52 views

Why do we get a three-dimensional output after a convolutional layer?

In a convolutional neural network, when we apply the convolution on a $5 \times 5$ image with $3 \times 3$ kernel, with stride $1$, we should get only one $4 \times 4$ as output. In most of the CNN ...
1
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1answer
30 views

Convolutional filters: create new ones

I'm studying a Master's Degree in Artificial Intelligence an my final work is about Convolutional Neuronal Networks. I was looking for information about filters (or kernel) at the convolutional ...
1
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1answer
30 views

Convolutional Neural Network: does each filter in each convolution layer create a new image?

Say I have a CNN with this structure: input = 1 image (say, 30x30 RGB pixels) first convolution layer = 10 5x5 convolution filters second convolution layer = 5 3x3 convolution filters one dense layer ...
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0answers
7 views

Looking for the right type of 1D-Convolution that only considers one column/attribute

My input has the shape of n rows (time steps) and m columns (attributes). I want to train a convolutional neural network on it to predict a class. I am currently using 1D-Convolutions. I got a good ...
0
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1answer
48 views

Why does Convolutional layer unde usually has the same input/output channel size?

As famous model VGG16 shows(and other famous models), The convolutional layers before pooling usually have the same input and output channel sizes? What's the reason for that? Is there a theory or ...
0
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2answers
133 views

How should the values of the filters of a CNN change?

I wrote a convolutional neural network for the MNIST dataset with Numpy from scratch. I am currently trying to understand every part and calculation. But one thing I noticed was the "just positive" ...
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0answers
34 views

How is the convolution operation used in CNNs a special case of the convolution operator?

How is the convolution operation used in convolutional neural networks (CNNs) a special case of the mathematical convolution operator? Most of us, when we think of the "convolution operation", we ...