SimGCD Read

Research Task Generalized Category Discovery (GCD) relaxes the assumption of traditional semi-supervised learning by assuming the unlabelled data can also contain different but related categories from the labelled data. The goal of GCD is to learn a model that is able to classify the already-seen categories in the labelled data, and more importantly, jointly discover the new categories in the unlabelled data and make correct classifications. Limitations of Previous Methods Previous methods can be categorized into two distinct approaches:

পোস্ট সমূহ