this post was submitted on 24 Apr 2024
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Machine Learning

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Hey guys,

I have been experimenting with self-supervised visual learning a bit. Until now I have only ever used U-Nets and related architectures.

No matter what specific task, images or other parameters I changed I always encountered these stains on my output-images (here marked with green), although sometimes more, sometimes less.

Now I wondered if anybody could tell me where they came from and how I could prevent them?

In the attached picture the input (left) and target (right) are the same, so that I can be sure these stains do not come from a badly designed learning task, yet they still appear (output is the middle image).

Thanks in advance and all the best :D

Edit: added line breaks

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[–] [email protected] 1 points 6 months ago

Thanks a lot, I will look into that :D