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GufyTheLire t1_j7ljbmj wrote

Do you expect the model to learn subtle details useful for classification from a relatively small training dataset? Wouldn't it be a better approach to train a defect detector for the model to know what is important on your images and then classify found features? Maybe this is the reason why large classification models are not widely used?

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johnGettings OP t1_j7lqkj2 wrote

Yes, definitely agree. The project started as one thing, then turned into another, then another. I was only doing the coin grading for fun and wasn't planning on actually implementing it anywhere. So I switched gears and just focused on building a high resolution ResNet, regardless of what would be best for the actual coin grading.

There are probably better solutions, especially for this size of a dataset, and maybe a sliding window is necessary to achieve very high accuracy.

But I think this model can still be useful and preferable for some datasets of large images with fine patterns. Or at the very least preferred for simplicitys sake.

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