Is there TensorFlow native function that does unpooling for Deconvolutional Networks ? I have written this in normal python, but it is getting complicated when want to translate it to TensorFlow ...

I'm currently building a GAN with Tensorflow 2 and Keras and noticed a lot of the existing Neural Networks for the generator and discriminator use Conv2D and Conv2DTranspose in Keras. I'm strugglin...

I noticed in a number of places that people use something like this, usually in fully convolutional networks, autoencoders, and similar: model.add(UpSampling2D(size=(2,2))) model.add(Conv2DTranspo...

What is the working of Output_padding in Conv2dTranspose? Please Help me to understand this? Conv2dTranspose(1024, 512, kernel_size=3, stride=2, padding=1, output_padding=1)

I am new to tensorflow for deep learning and interested in deconvolution (convolution transpose) operation in tensorflow. I need to take a look at the source code for operating deconvolution. The f...

I have seen two ways of visualizing transposed convolutions from credible sources, and as far as I can see they conflict. My question boils down to, for each application of the kernel, do we go fr...

I am trying to deconvolve complex gas chromatogram signals into individual gaussian signals. Here is an example, where the dotted line represents the signal I am trying to deconvolve. I was able ...

I am trying to deblur an image in Python but have run into some problems. Here is what I've tried, but keep in mind that I am not an expert on this topic. According to my understanding, if you know...

Here in this code UpSampling2D and Conv2DTranspose seem to be used interchangeably. I want to know why this is happening. # u-net model with up-convolution or up-sampling and weighted binary-cros...

I would like to use the Keras layer: from keras.layers.convolutional import UpSampling2D x = UpSampling2D((2, 2))(x) How can I replicate this behavior with native tensorflow ? I can't manage ...

I'm novice on r-cnn. There are term AP, AP50, AP75 on mask r-cnn paper. 50, 75 is small postfix, but I can't make it small, sorry. Anyway the paper says it is averaged over IOU thresholds. For AP50...

I am attempting to create a deep CNN that can classify each individual pixel in an image. I am replicating architecture from the image below taken from this paper. In the paper it is mentioned that...

I have created a Deep Convolution Neural Network to classify individual pixels in an image. My training data will always be the same size (32x32x7), but my testing data can be any size. Github Rep...

I am trying to implement a convolutional neural netwrok and I don't understand why using im2col operation is more efficient. It basically stores the input to be multiplied by filter in separate col...

Using MetalKit for iOS 10, when we try to perform MPSCNNConvolution, with inputs as following : Kernel Size : 16x16 Input channels : 300 Output channels : 250 Dimensions of input image : 250x250...

I'm trying to develop a deconvolutional layer (or a transposed convolutional layer to be precise). In the forward pass, I do a full convolution (convolution with zero padding) In the backward pas...

In the paper 'Fully Convolutional Networks for Semantic Segmentation' the author distinguishes between input stride and output stride in the context of deconvolution. How do these terms differ fro...

This is a really weird error, partly a follow-up to the previous question(Deconvolution layer FCN initialization - loss drops too fast). However I init Deconv layers (bilinear or gaussian), I get...

I'm training a small (10M weights on 12K images) FCN (see e.g. Long et al, 2015). The architecture is the following (it starts with FCN8s fc7 layer): fc7->relu1->dropout->conv2048->co...

I'm trying to understand scipy.signal.deconvolve. From the mathematical point of view a convolution is just the multiplication in fourier space so I would expect that for two functions f and g: D...

This layer in not ready documented very well and I'm having a bit of trouble figuring out exactly how to use it. I'm Trying something like: input_img = Input(shape=(1, h, w)) x = Convolution2D(16...

I'm trying to stack 2 layers of tf.nn.conv2d_transpose() to up-sample a tensor. It works fine during feed forward, but I get an error during backward propagation: ValueError: Incompatible shapes fo...

Here is my problem: I am going to process data coming from a system for which I will have a good idea of the impulse response. Having used Python for some basic scripting before, I am getting to kn...

Recently I began to study deconvolution algorithms and met the following acquisition model: where f is the original (latent) image, g is the input (observed) image, h is the point spread functio...