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I am currently working on a project in which i'm supposed to classify whether an image contains a translucent watermark or not. This is hard to do with standard object classification or template matching because of the translucency and very low image quality.

I thought about generating a dataset with the watermark pasted somewhere on the image. Given enough generated data, could I train a neural network to classify the real images? If not, why not? Thank you for your help.

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  • $\begingroup$ You may want to use spatial transformers, but you may need a lot of data. $\endgroup$ – Media Nov 24 '18 at 17:24

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