A Beginners Guide to Deep Metric Learning

Learning the similarity between objects has a dominant role in human cognitive processes and artificial systems for recognition and classification. Using an appropriate distance metric, the metric learning attempts to quantify sample similarity while conducting learning tasks. Metric learning techniques, which typically use a linear projection, are limited in their capacity to tackle non-linear real-world scenarios. Kernel approaches are employed in metric learning to overcome this problem. In this post, we will understand what metric learning and deep metric learning are and how deep metric learning can address the challenges faced by metric learning. We will also explore in this post how metric learning can be used in practice. The major points to be discussed in this article are outlined below. Table of Contents  Working of Various Learning SchemesWhat is Metric Learning?Deep Metric LearningImportant Points of Deep Metric Learning  Let’s start the discussion by