A mathematical operation that combines two signals to generate a third signal.
How is the convolution operation carried out when multiple channels are present at the input layer? (e.g. RGB) After …
computer-vision artificial-intelligence neural-network convolutionHere in this code UpSampling2D and Conv2DTranspose seem to be used interchangeably. I want to know why this …
machine-learning computer-vision conv-neural-network convolution deconvolutionThe theory from these links show that the order of Convolutional Network is: Convolutional Layer - Non-linear Activation - Pooling …
neural-network theano convolutionI want to implement some image-processing algorithms which are intended to run on a beagleboard. These algorithms use convolutions extensively. …
c signal-processing fft convolution beagleboardSay we have a single channel image (5x5) A = [ 1 2 3 4 5 6 7 8 9 2 1 4 5 6 3 4 5 6 7 4 3 4 5 6 2 ] And a filter K (2x2) K = [ 1 1 1 1 ] An example of applying convolution (…
rgb matrix-multiplication convolution dot-productFirst of all here is my github link for the question. And here is my question: I would like to …
python opencv neural-network convolution face-recognitionI've used Scikit-learn's GridSearchCV before to optimize the hyperparameters of my models, but just wondering if a similar tool exists …
python tensorflow convolution hyperparametersI'm just beginning my ML journey and have done a few tutorials. One thing that's not clear (to me) is …
machine-learning neural-network keras conv-neural-network convolutionThese two tasks are popular applications of convolutional neural networks. However, I don't understand the difference. According to one Caffe …
neural-network convolution deep-learningI would like to take two images and convolve them together in Matlab using the 2D FFT without recourse to …
matlab image-processing convolution