Deep Metric Learning

Deep metric learning is a technique in machine learning where a neural network learns to measure how similar or different two data points are. Instead of just classifying items into categories, it maps them into a mathematical space where similar items are close together and dissimilar ones are farther apart. For example, it can help facial recognition systems distinguish between different people by learning the subtle features that set them apart. This approach improves the system's ability to find and compare items based on their inherent attributes, enabling more flexible and accurate tasks like object recognition, recommendation systems, and biometric identification.