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I have a number of .jpeg from the websites of musicians. These images are comprised of posters for upcoming shows and band photos (photos of the band in real life).

Here is an example poster:

enter image description here

I am not well-versed in any modern techniques or algorithms (if they exist?), but this is what I thought I might look for:

  • Text in the image is usually a dead giveaway of a poster.

  • Maybe realistic photos (ie. non-posters) follow a different color distribution?

  • Posters are probably less likely to have faced in them - but that's a pretty weak assertion.

Is there any classification algorithm that can detect if an image is a poster?

1 Answer

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by (92.8k points)

You can use ImageNet as your approach to solving your query.

Nowadays, these convolutional neural networks are everywhere. Facebook uses them to tag the photos, self-driving cars are using them to detect objects; basically, anything that knows what’s in an image or video can use them. Through the ImageNet approach, you can tell what’s in an image by finding patterns between pixels on ascending levels of abstraction, using thousands to millions of tiny computations on each level. The new images can be put through the process to match their patterns to the learned patterns of the model. 

For more information regarding the ImageNet, refer the following link: https://qz.com/1034972/the-data-that-changed-the-direction-of-ai-research-and-possibly-the-world/

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