# Questions tagged [convolution]

For use when discussing the commutative and linear, but not associative operator interpreted on functions and distributions.

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### What are filter values in subsequent convolutional layers?

Suppose we have the filters for face detection as a combination of eye, nose, and mouth filters. Does this mean we only need to learn the filter values for the nose, eye, and mouth filters, since the ...
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### ResNet output dimensions of initial convolution don’t yield in an integer

I am trying to understand the ResNet dimensions, but got stuck at the first layer. We are passing a [224x224x3] image into 64 filters with kernel size 7x7 and stride=2. According to the ResNet source ...
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### when depthwise separable convolution should be preferred over normal convolution?

As a novice in the realm of deep learning, I recently learned about Depthwise Separable Convolution. I have seen some tutorials and articles about it on internet, and in all of them the author ...
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### Understanding, visualizing and interpreting CNN activations

I am working with the first layer of a CNN and trying to understand how to interpret the activation output. My CNN takes input from 3 channels (RBG picture) and the first layer is ...
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### Understanding scipy.signal.convolve2d full convolution and backpropagation between convolutional layers

I'm learning about convolutional neural networks. The convolution operation in order to extract features that is described in literature and posts used for this is quite intuitive and easy to ...
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### What will be the input_shape of tf.keras.layers.Conv3D be for these inputs

I have many videos, and each video is made up of 37 images (there are 37 frames in the whole video). And the dimension of each image is (100, 100, 3).... So the ...
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### Finding optimal time series using convolution [closed]

we logged sensor data while milling a workpiece. At several points, the workpiece was damaged and this induced a certain sensor data time series. Due to noise and since its a real world measurement, ...
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### Pytorch: Reduce forward prediction dimensions of GRU network / Improving Network Architecture

I am currently working on a GRU network to predict a time series, please note that I am completely new to machine learning and pytorch. Also I have never had a formal education in programming. This ...
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### Trade-off between number of channels and size of convolutional filters

As far as I understand, the common practice in the modern CNN architectures is to use a smaller convolutional filters, but deeper networks with more channels. One of the reason behind this is that one ...
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### Are convolutions in deep learning associative?

Let's denote "convolution in deep learing" as "convolution-deep", and "convolution in math or signal processing" as "convolution-math". As we all know, ...
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### Does a Convolutional Layer in a Neural Network learn the correlation between its input signals via its kernel?

I am interested in the theory behing what a convolutional neural network learns with its convolutional operations. I think it learns (useful) kernels which measure the correlation between its input ...
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### What features used by CNN model should a feature store actually store? [closed]

According to MLOPs principle, it is recommended to have a feature store. The question is in the context of doing image classification using deep learning models like convolutional neural networks ...
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### Are 3D kernels in convolutions summed over their channels?

Say for example that I have a 28x28x1 grey scale image and I will perform two consecutive convolutions. The first convolution has 2 3x3x1 filters and the second has 3 3x3x2 filters. Each convolution ...
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### Utilizing 1x1(x1) convolutions as a learned max pooling (3D)?

I have a semantic segmentation network that ingests 3D images (hyperspectral $(x, y, b)$) and predicts 2D images (semantic map $(x, y)$). This network takes the form of a classic UNet, though it ...
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### Changing order of input dimension in Tensorflow 3-D Layers

According to the official documentation of tf.keras.layers.Conv3D 5+D tensor with shape: batch_shape + (channels, conv_dim1, conv_dim2, conv_dim3) if data_format='channels_first' or 5+D tensor with ...
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### Can I say that a trained neural network model with less parameters requires less resources during real world inference?

Let us imagine that we have two trained neural network models with different architectures (e.g., type of layers). The first model (a) uses 1D convolutional layers with fully-connected layers and has ...
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### Comparison of different ways of Upsampling in detection models

There are various ways to increase the resolution of tensor in (width, height) dimensions, frequently used in detection models like ...
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### Should kernel size always be a prime number?

Should kernel size always be a prime number? E.g. (3,3) (5,5) (7,7). While tinkering with sklearn.preprocessing.KernelCenterer(), I noticed that I could only get it ...
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### Notation of Transposed Convolution Operation in Equation

How do I notate a transposed convolution operation (as it is used in deep learning), in a math equation? A convolution operation for example is often notated as $\hat{y} = x \circledast W$ where $W$ ...
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### About the relevance and interprertability of convolutional filters?

Convolution filters are known to perform very well in tasks, concerning some work with the image or video data, due to their ability to preserve some spatial information and equivariance property ...
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### Autocorrelation of two functions multiplied and raised to arbitrary powers

Given a signal $A$ and a signal $B$ with autocorrelation times of $\tau_A$ and $\tau_B$, respectively, where $\tau_A > \tau_B$, is there any general statement that can be made about the ...
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### Extended ResNet

The success of ResNet is mainly ascribed to the fact that it is very easy for deeper networks to learn the identity function hence there's little risk when the network becomes too deep. I was ...
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### Will disparity in image format/quality between binary classifications affect training of Convolutional Neural Network?

I have an image dataset containing two classes. One of the classes has many images and they are all JPG images with the following format: ...
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### Error after merging two Deep Learning models VGG16 and ResNet50

I have merged two different models namely VGG16 and ResNet50 and given the outputs of the two models as input to another model. I have checked the Layers graph is correct. Before merging the code was ...
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### Adapting ZFNet on 2244x224 image using a filter 7X7

I am building a model based on ZFNet in Tensorflow 2.0. I am using the Petal images dataset. The images are of size 224x244x3. So my question is when implementing the first layer (conv2d) with filter ...
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### There are 2 figures explaining transposed convolution. Which one is correct?

I have been struggling to understand transposed convolution. When I search for "transposed convolution", there are 2 figures explaining transposed convolution in which I think are not ...
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### Why is everybody using mobilenetv2 for mask detection?

I was looking for good pre-trained models to be used for mask detection and I found resnet50 and mobilenetv2 (lots of times). ...
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### ValueError: Input 0 of layer sequential is incompatible with the layer: expected ndim=3, found ndim=4. Full shape received: [None, 25, 25, 1]

I am trying to use conv1D but getting that error. My dataset's is batched and has a shape of [None, 25, 25, 1] I am using input_shape=(25,25) I am not able to figure out what should I change so I can ...
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### Can anyone recommend me a very good pre-trained model for face or head detection?

I really need to know the best pre-trained models to detect faces and/or peoples' head. Not a face recognition model, but only to classify whether an object is a person's head/face or not. I'm ...
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### Can convolutional network learn structural properties of one feature w.r.t to other?

I'm going through the literature on pose-estimation ( DeeperCut, OpenPose, MultiPersonPosetrack). I'm interested in knowing whether these networks/ generally a CNN can learn properties (geometrical) ...
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### What does it mean to say convolution implementation is based on GEMM (matrix multiply) or it is based on 1x1 kernels?

I have been trying to understand (but miserably failing) how convolutions on images (with height, width, channels) are implemented in software. I've heard people say their convolution implementation ...
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### Understanding image size changes in DCGAN

I have been studying and trying to implement Generative Adversarial Networks using PyTorch. More precisely I tried to replicate the DCGAN PyTorch Tutorial tutorial using some custom dataset. My code ...
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### Strategy for improving performance of 3D convolutional GAN

Others working with neural nets and GAN's might find this question interesting. Background: I've been working with data from Berkeleys PEER Ground Motion Database to generate new novel seismic traces. ...
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### Can I tune a model after training it? (Convolutional Neural Network & Classification)

I am relatively new to Data Science and I've recently embarked on a project. Long story short, I've trained a CNN model to distinguish between Male and Female genders. However, I wish to tune my model....
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### How to perform upsampling (and NOT interpolation) process theoretically modelled?

As an example, I know that sampling a signal $s$ is modelled by multiplication of s by a dirac comb, which has the effect of convolving the Fourier Transform (FT) of $s$ by the FT of the dirac comb ...
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### How to backpropogate Convolution layer padding inputs with respect to output derivative

I created a convolution network with 5 Conv blocks, let discuss the issue based on Conv block 4 & 5 Conv Block 4 Input Image size : 28 * 28, Padding size 1 : 30 * 30 (image size ...