DIGITAL MEETUP RECORDING
Similarity is a strange notion: it’s the same, but different. You probably don’t lose any sleep over it, but how could a deterministic algorithm deal with it?
This presentation will show how you can build deep neural networks that quantify similarity between images, and allow downstream tasks like content search or data clustering. We’ll also get an understanding for how the data is represented in the networks, and why this works in the first place.
Does ”similar” actually have a very specific meaning to you? There are many techniques out there to fine-tune networks for similarity, whether you have labeled ground truth examples or not.
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