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Questions tagged [feature-maps]

For questions related to the concept of a feature map in the context of convolutional neural networks.

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Why CNN filters (kernels) are randomly initialized?

I learned that when CNN filters are defined, they are initialized with random weights and bias(Im not sure about bias). Then as learning step goes on, the weight values change and each filter makes ...
COTHE's user avatar
  • 5
0 votes
2 answers
975 views

How do we combine feature maps? CNN

In Convolutional Neural Networks we extract and create abstractified “feature maps” of our given image. My thought was this: We extract things like lines initially. Then from different types of lines ...
Brian Przezdziecki's user avatar
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1 answer
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combine two features in dataset?

I have a data set containing the number of security gaps and the level of that gap for a specific website. Now suppose I have 2 features in this data set, the first feature is the number of a ...
Issa Mansour's user avatar
1 vote
0 answers
47 views

What are the recommended ways to change shape of feature maps channel wise other than using Convolutional neural networks?

Suppose I have a feature map with size $C_1 \times H \times W$. And I need to convert it into a feature map of size $C_2 \times H \times W$. One way to do this is to use convolutional neural networks ...
hanugm's user avatar
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1 vote
1 answer
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How is the depth of the filters of convolutional layers determined? [duplicate]

I am a bit confused about the depth of the convolutional filters in a CNN. At layer 1, there are usually about 40 3x3x3 filters. Each of these filters outputs a 2d array, so the total output of the ...
FourierFlux's user avatar
16 votes
1 answer
5k views

What is the difference between a receptive field and a feature map?

In a CNN, the receptive field is the portion of the image used to compute the filter's output. But one filter's output (which is also called a "feature map") is the next filter's input. What's the ...
Monica Heddneck's user avatar
7 votes
2 answers
181 views

CNNs: What happens from one neuron volume to the next?

I've gone through several descriptions of CNNs online and they all leave out a crucial part as if it were trivial. A "volume" of neurons consists of several parallel layers ("feature ...
MackTuesday's user avatar
4 votes
3 answers
7k views

How is the depth of a convolutional layer determined?

I am looking at a diagram of ZFNet below, in an attempt to understand how CNNs are designed. In the first layer, I understand the depth of 3 (224x224x3) is the number of color channels in the image. ...
OnNIX's user avatar
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