Facial recognition with unbalanced dataset
I'd like to perform facial recognition. I have very few images of a person I need to recognize. Is there a way to improve accuracy with a small size of imagery training data?
Answers
Maybe you could increase your dataset by manipulating the existing images (crop, make darker, make more blurrish, etc.)
Beneath this there are quite a lot articles out there regarding "Transfer Learning" or "Inductive Transfer" were you use a pretrained net that can detect certain features and then adapt it to your task by keeping some weights stable (feature detectors) and fine adjusting only the weights of the back layers (Google for "neural network small dataset").
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Just came across these courses on YouTube: Convolutional Neural Networks (Course 4 of the Deep Learning Specialization) Especially these 3 lessons starting with "One shot learning" explain an interesting approach to face recognition.
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