Top "Convolution" questions

A mathematical operation that combines two signals to generate a third signal.

Inverse convolution of image

I have source and result image. I know, that some convolution matrix has been used on source to get result. …

image algorithm convolution
Is there a Python equivalent of MATLAB's conv2 function?

Does Python or any of its modules have an equivalent of MATLAB's conv2 function? More specifically, I'm interested in something …

python matlab matrix convolution
CUDA small kernel 2d convolution - how to do it

I've been experimenting with CUDA kernels for days to perform a fast 2D convolution between a 500x500 image (but I …

c++ image image-processing cuda convolution
What does kernel_constraint=max_norm(3) do?

In one of the tutorials I am working on (link given below), the author outlines the baseline neural network structure …

optimization computer-vision keras conv-neural-network convolution
Defining model in keras (include_top = True)

Can somebody tell me what include_top= True means when defining a model in keras? I read the meaning of …

python neural-network keras convolution
Fully-connected layer weight dimensions in TensorFlow ConvNet

I've been coding along this example of a convolution net in TensorFlow and I'm mystified by this allocation of weights: …

convolution tensorflow conv-neural-network
1D Fast Convolution without FFT

I need an 1D Convolution against 2 big arrays. I'm using this code in C# but it takes a loooong time …

c# optimization convolution
Difference between Conv2D and Convolution2D in Keras

There is already an answer wrt to Tensorflow. But the problem is that In my IDE Conv2D is a …

machine-learning neural-network keras convolution keras-layer
How can I determine if my convolution is separable?

What makes a convolution kernel separable? How would I be able to tell what those separable parts were in order …

math image-processing signal-processing convolution
For what reason Convolution 1x1 is used in deep neural networks?

I'm looking at InceptionV3 (GoogLeNet) architecture and cannot understand why do we need conv1x1 layers? I know how convolution …

neural-network tensorflow deep-learning convolution conv-neural-network