It would be great to know the classification accuracy on pictures that you yourself take on a campus tomorrow. I can imagine that your classifier did not only learn the features of a face but also certain camera properties (contrast, brightness, …) as you were crawling websites of institutes that tend to take pictures of their staff with the same camera. What do you think?
Yes, you're absolutely right. Also, some institutes might take photos of their staff in front of the same background, with same lighting, etc. These are features that might bias the model.
Taking pictures on campus by myself is infeasible, but I could try to have test data, which consists purely of pictures from "unseen" institutes / departments.
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Hi Ferdinand, very nice project, good work!
It would be great to know the classification accuracy on pictures that you yourself take on a campus tomorrow. I can imagine that your classifier did not only learn the features of a face but also certain camera properties (contrast, brightness, …) as you were crawling websites of institutes that tend to take pictures of their staff with the same camera. What do you think?
Anyway, great project!
Yes, you're absolutely right. Also, some institutes might take photos of their staff in front of the same background, with same lighting, etc. These are features that might bias the model.
Taking pictures on campus by myself is infeasible, but I could try to have test data, which consists purely of pictures from "unseen" institutes / departments.