My research task is face recognition in cars with using deep learning method. Actually, in example we set an driver randomly and then the question is: Is this person driver or not?
So i created an custom dataset that includes 47 different persons's faces when they are driving cars. Every person's have 3000 face images and I used MTCNN for detect faces from images.
But I'm confused; is the problem multi-class classification or binary? I mean the result is binary (driver or not) but we'll set driver after created this model. for that I can not divide the dataset like driver and others.
When I researched I found that one-class classification approach. Deep One-Class Classification Is this help me or not, I don't get it.
What I should do?