Is Semi-Supervised Learning The Future Of Image & Video Classification?

Developers are constantly enhancing artificial intelligence capability by leveraging various machine learning methodologies like supervised, unsupervised, and reinforcement learning. More recently, Facebook used supervised learning for state-of-the-art image and video classification. They call their new approach as semi-weak supervision, where the firm combined semi-supervised learning and weakly supervised learning to achieve a new benchmark in image classification.  Facebook boasts that their method will be able to deliver effective results even when there is a dearth of high-quality labelled training data. Semi-Weak Supervision Citing several drawbacks like inherent noise, missing and irrelevant tags etc, in training models with weak supervision, Facebook used the teacher-student model training paradigm. They leveraged billions of unlabelled images along with a relatively smaller set of task-specific labelled data. Initially, they trained on labelled data to get a teacher