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i have some queries regarding your implementation.
why did you use the deconv operation 5 times in fcn32, slowly upsampling gives better resultsd than a single conv2d operation?
also, can you please give me some reference how to study about using pretrained weights for custom model. your usage of pretrained weights is good. I want to learn. Can you please give me some inputs. I built a simple fcn model and used pretrained models as follows:
model = fcn()
model.load_state_dict(model_zoo.load_url(model_urls['resnet50']), strict=False)
it gives better result, but i am not sure how it uses the weights. whether based on layer names or automatic concat weights based on kernel size.
thank you
The text was updated successfully, but these errors were encountered:
hello author,
i have some queries regarding your implementation.
model = fcn()
model.load_state_dict(model_zoo.load_url(model_urls['resnet50']), strict=False)
it gives better result, but i am not sure how it uses the weights. whether based on layer names or automatic concat weights based on kernel size.
thank you
The text was updated successfully, but these errors were encountered: