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thanks for your patience, this is a new community and surely the answers will come much quicker.
VisualTest uses a variety of algorithms to find visual regression bugs. As of today, for the web app comparisons we break the problem down to 3 parts:
1. object detection (what are the visible elements on screen)
2. object quantification (how does it look? what is it like?)
3. object matching (what happened to each element across these two versions)
we use various techniques for each section of the problem, but the end result is that you get a content aware comparison across the 2 versions of your app's screenshots.
As we have an in house data science team, we are also fine tuning our deep learning models for release sometime next year in preparation for native mobile app support.
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