Questions tagged [u-net]

Question 1

I have a binary image that is the Canny output of an image containing some objects and my goal is to learn to recognise the corners of the objects and measure the perimeters. Example: The goal is to ...

Question 2

I'm implementing Algorithm S.1 (Pixel Ground Truth Generation) from the ARU-Net paper by Grüner et al., but I'm having trouble understanding a few key steps in the context of non-linear (curved) ...

Question 3

The initial validation loss is low from the first epoch and then decreases slightly. What does this actually mean? Does it indicate that the model can effectively and quickly identify patterns for ...

Question 4

I have a bunch of images of cells from a brightfield microscope that I want to segment. Cells have different morphologies, shapes, etc. depending on cell lines. I also have some metadata associated ...

Question 5

I am recently implementing DDPM model from scratch, and I discovered that UNet often tends to give noisy output in blank region. Here is an example with FashionMNIST, my DDPM seems to generate OK ...

Question 6

I had lidar 3D point cloud data from semantckitti. I want to perform Semantic Segmentation on the data using U-Net. I converted the 3d point cloud data into 2D using spherical conversion and saved the ...

Question 7

When adding noise to an image, for instance, is the noise added evenly random (equally likely values within some range), or random but following some distribution (like the normal distribution)? Then,...

Question 8

I have a variational convolutional autoencoder that has trained on 2 images and outputs a linear interpolation (inserted at the bottleneck stage) between those 2 input images. However, the result ...

Question 9

I wrote simple 3D-Unet arch in pytorch to do segmentation on 3D images. ...

Question 10

I am looking to create a model that is able to perform binary segmentation of images with varying resolutions. For model should be able to classify tree or not tree regardless of the resolution of the ...

Question 11

I come from a math background, so I am not up-to-date with machine learning literature. For the purpose of learning dynamics, I would like to train a model to minimize the following loss: $$\mathcal{L}...

Question 12

I was able to find that the skip connections used in U-Net help to recover fine grained details in the prediction, however I do not understand what is meant by this. Besides, I was wondering what ...

Question 13

I want to know why diffusion models always use U-Net. In my opinion, they use U-Net because you can see features of different resolutions and skip connection is good to add detail of images. But I am ...

Question 14

I am trying to train networks to achieve what I expected to be a trivial task: learn the identity mapping. However, this is very hard to achieve, and the optimization is hard. Moreover, I don't want ...

Question 15

Hello I'm implementing a CycleGAN and most of the other implementations I've seen on the internet use Convolution with stride 2 instead of a Maxpoolinglayer for downsample. On to my question, why ...

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Questions tagged [u-net]

neural network for learning the permeter of objects from binary images

How to compute local text orientation and interline distance for curved baselines in ARU-Net (Algorithm S.1)?

Low validation loss from the first epoch?

Adding extra parameters to the inputs of a network?

Why does UNet often output noisy pattern in blank/homogeneous region?

How do I input multi-channel Numpy array to U-net for semantic segmentation

How to remove random noise from an image (denoising)?

How to perform latent space Interpolation between two images?

3D Unet gives "output size is too small" error [closed]

Image segmentation with varying resolution

Which models can be applied recursively?

What is the role of skip connections in U-Net?

Why diffusion model always use U-Net?

Learning an identity function with convolutional networks

U-Net Maxpooling vs Convolution

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