Questions tagged [pooling]

For questions related to the concept of pooling (e.g. max-pooling), aka downsampling, in the context of convolutional neural networks.

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Is there any closed form analytical expression to represent fractional max pooling?

There are Nineteen pooling layers in PyTorch. Almost all of the layers are provided with corresponding analytical formulae. But analytical formulae is not provided for the fractional max pooling ...
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DeepLabV3: Why use global average pooling in the ASPP module?

I'm trying to understand the rationale of the various modifications the authors of the DeepLab models have made to their third version, DeepLabV3. In the paper, the following is written: ASPP with ...
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Is strided 2d pooling using only reshape and slice operations possible

Is it possible to do strided 2d pooling using only reshape and slice operations? In a nutshell, can you do strided 2d pooling using only np.reshape and slice (eg. <...
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What are the purposes of pooling in CNNs?

There are three questions on this site related to this What is the effect of using pooling layers in CNNs? Is pooling a kind of dropout? What are the benefits of using max-pooling in convolutional ...
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1answer
32 views

Is average pooling equivalent to a strided convolution with a specific constant kernel?

It seems to me that average pooling can be replaced by a strided convolution with a constant kernel. For instance, a 3x3 pooling would be equivalent to a strided convolution (of stride $3$) with a $3 \...
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1answer
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What is the time complexity of the upsampling stage of the U-net?

I am trying to determine the complexity of the neural network we use. The neural network is a U-net generator with an input shape of NxN (not an image but image-like data) and output of the same shape....
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51 views

Since both RoI Align and PrRoI Pooling use bilinear interpolation, why is RoI Align discrete while PrRoI Pooling continuous?

I have two questions. Since both use bilinear interpolation, why is RoI Align discrete while PrRoI Pooling continuous? Could anyone explain the intuition behind the derivative of PrPool()?
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How can the FCNN reduce the dimensions of the input from $1048 \times 100$ to $523 \times 100$ with max-pooling?

I am trying to implement a paper on Image tempering detection and localization, the paper is Image Manipulation Detection and Localization Based on the Dual-Domain Convolutional Neural Networks, I was ...
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1answer
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In Fast R-CNN, how are input RoIs mapped to the respective RoIs in the feature map before RoI pooling?

I've been reading the Fast R-CNN paper. My understanding is that the input to one forward pass is the whole input image plus a list of RoIs (generated by selective search or another region proposal ...
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288 views

Can CNNs be applied to non-image data, given that the convolution and pooling operations are mainly applied to imagery?

When using CNNs for non-image (times series) data prediction, what are some constraints or things to look out for as compared to image data? To be more precise, I notice there are different types of ...
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1answer
65 views

How can max-pooling be applied to find features in words?

I'm reading about max-pooling in a dynamic CNN paper. I can see how it can help find features in images, given that the pixel with the highest density gets pooled, but how does it help to find ...
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Is pooling a kind of dropout?

If I got well the idea of dropout, it allows improving the sparsity of the information that comes from one layer to another by setting some weights to zero. On the other hand, pooling, let's say max-...
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87 views

Why do we have to dot product in the Low-rank Bilinear Pooling?

I was reading this paper Hadamard Product for Low-rank Bilinear Pooling. I understand what they are trying to say, but I don't know why we have to convert the element-wise multiplication into a scalar ...