Questions tagged [u-net]

For questions related to the U-net, a neural network proposed in "U-Net: Convolutional Networks for Biomedical Image Segmentation" (2015) by Olaf Ronneberger et al. for semantic segmentation.

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Model output segmentation maps which are not full

I created a VGG based U-Net in order to perform image segmentation task on yeast cells images obtained by a microscope. There are a couple of problems with the data: There is inhomogeneity in the ...
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1answer
54 views

What is the time complexity of the upsampling stage of the U-net?

I am trying to determine the complexity of the neural network we use. The neural network is a U-net generator with an input shape of NxN (not an image but image-like data) and output of the same shape....
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1answer
45 views

How to quickly change hand-drawn shapes to symmetrical polished shapes?

Given a hand-drawn shape, I'd like to generate the corresponding symmetrical polished shapes such as circle, rectangle, triangle, trapezoid, square, parallelogram, etc. A short video demonstration ...
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0answers
39 views

Is it necessary to label the background when generating the labelled dataset for semantic segmentation?

When I label images for semantic segmentation (using u-net, if that matters), is labeling the background (anything I am not interested in) necessary? Will it improve the network's performance?
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30 views

Suppress heatmap non-maxima in segmentation with UNet

I'm using U-Net for image segmentation. The model was trained with images that could contain up to 4 different classes. The train classes are never overlapping. The output of the UNet is a heatmap (...
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0answers
18 views

How can I extract images features in k-few shot learning to do semantic segmentation?

I've just started to learn N-way k-few shot learning, and I have understood how to use, i.e., Prototypical networks or Siamese networks to classify images. But, if I want to use those networks to do ...
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1answer
407 views

What are some good alternatives to U-Net for biomedical image segmentation?

Soon I will be working on biomedical image segmentation (microscopy images). There will be a small amount of data (a few dozens at best). Is there a neural network, that can compete with U-Net, in ...
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1answer
89 views

Why everyone is using CNN for image segmentation?

I'm a newbie in artificial intelligence. I have started to research how to do image segmentation and all the papers that I have found are about CNN. Most of them use the same network, U-net, but with ...
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0answers
24 views

How to train image segmentation task with only one class?

Is there a neural network that has architecture optimizations for segmenting only one class (object and background)? I have tried U-net but it is not providing good enough results. I am wondering if ...
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0answers
30 views

Using U-NET for image semantic segmentation

I'm getting literally crazy trying to understand how U-NET works. Maybe it is very easy, but I'm stuck (and I have a terrible headache). So, I need your help. I'm going to segment MRI to find white ...
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0answers
7 views

Would models like U-Net be able to segment objects which has label based on its surrounding context?

Suppose that we want to segment a red blob from the image, normally you will have a class for this red blob e.g. 0. And every red blob you detected will have a class of 0. But, in my case, I want ...
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2answers
93 views

What are the best algorithms for image segmentation tasks?

I recently started looking for networks that focus on image segmentation tasks related to biomedical applications. I could not miss the publication U-Net: Convolutional Networks for Biomedical Image ...
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31 views

What are some neural network models that can use auxiliary info during training for image segmentation?

What are some deep learning models that can use supplementary information other than RGB channels for image segmentation? For example imagine a poorly shot image of a river (blue) that shows a gap, ...
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0answers
260 views

How can I use the bottleneck layer of the U-net to calculate the similarity between two images?

I would like to use the bottleneck layer of U-Net (the last layer of the encoder) to calculate the similarity between two images. For that, I have to somehow flatten the last layer of the encoder. In ...
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0answers
11 views

How do we stack two U-Nets to yield one final prediction?

I am trying to reproduce the model described in the paper DocUNet: Document Image Unwarping via A Stacked U-Net, i.e. stacking two U-Nets to yield one final prediction. The paper mentions that: ...