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Segmentation algorithm not giving correct output

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Shoaib Ali
Shoaib Ali le 4 Août 2022
Commenté : Shoaib Ali le 12 Sep 2022

Hi ,
I am evaluating segmentation models with my own data. Only FCN produces the right segmented output for test images, but other segmentation models (such as U-Net and SegNet) produced really odd results. The segmented pixels are dispersed throughout the whole image instead of the targeted region. Even if I evaluate my trained model using the training data.
What may be the reason behind that?
This is segmented output by SegNet.

This is segmented output by FCN.

Réponses (1)

Birju Patel
Birju Patel le 8 Sep 2022
Generally, FCN, U-Net, and SegNet are different architectures that require their own set of training options to produce optimal results. You cannot assume they will all converge to the same results.
For instance, U-Net does not use a pre-trained backbone so it can take longer to train compared to FCN, which uses a VGG-16 image net pretrained backbone.
  1 commentaire
Shoaib Ali
Shoaib Ali le 12 Sep 2022
Thank you for your answer.
You mean I have to train each network with diffferent hyperparameters to figure out the best values of parameters for each model?

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