Scared_Employer6992 OP t1_ja7xpjt wrote on February 27, 2023 at 2:49 PM

Reply to comment by QuadmasterXLII in [D] Training a UNet-like architecture for semantic segmentation with 200 outcome classes. by Scared_Employer6992

I haven't tried with bs=1, but I also don't want to use bs=1 as I usually get bad results with it and my net has a lot of BN layers.

badabummbadabing t1_ja7yxbg wrote on February 27, 2023 at 2:58 PM

Don't use batch normalization. Lots of U-Nets use e.g. instance normalisation. A batch size of 1 should be completely fine (but you will need to play with the learning rate upon changing this). Check the 'no new U-Net' (aka NN-Unet) paper by Fabian Isensee for the definitive resource on what matters in U-Nets.

LetterRip t1_ja88v3i wrote on February 27, 2023 at 4:06 PM

Which particular paper?

badabummbadabing t1_ja8bzhc wrote on February 27, 2023 at 4:27 PM

https://cardiacmr.hms.harvard.edu/files/cardiacmr/files/isensee_etal_nature2021_nnunet.pdf Check Figure 4. Architecture barely matters on average.