tutorial on domain adaptation and transfer learningA large part of the computer vision literature focuses on obtaining impressive results on large datasets under the main assumption that training and test samples are drawn from the same distribution. However, in several applications this assumption is grossly violated. Think about using algorithms trained on clean Amazon images to annotate objects acquired with a low-resolution cellphone camera, o
