Comments (5)
Hi,
I have read an article mentioned an algorithm for training text recognition model called curriculum learning. I think it matches your idea. This is the title of the paper: Rosetta: Large Scale System for Text Detection and Recognition in Images.
I hope it helps.
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Thanks for the answer, I just checked out the articles and it seems interesting! But I wonder if it will work in our case. Feeding the algorithm little by little will that really bring high accuracy?
But I guess going with Holmeyoung's idea about large dataset = better answer in this case is probably the right thing.
But due to my machine's limits and since I'm using google colab (12 hours free gpu use only) as a tool for DL is giving me a disadvantage here when creating a large dataset 😌 That's why I thought about this idea.
Anyways, thanks a lot for the answer 😄 Also do you recommend any DL tools/environnement?
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Yes, it is worth it.
Goodluck.
from crnn-pytorch.
No problems. Actually, I am using paperspace, but it is not free unfortunately 😌.
from crnn-pytorch.
Hehe I see,it's troubling right 😅
Well, it's worth it when your program work 😊
Thanks for the suggestion and the answer :)
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Related Issues (20)
- KeyError : ' ' HOT 1
- Problem loading checkpointed model
- inference accuracy HOT 10
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- create image Tensor HOT 2
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- number images train
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