![]() ![]() Modern face recognition systems approach the problem of one-shot learning via face recognition by learning a rich low-dimensional feature representation, called a face embedding, that can be calculated for faces easily and compared for verification and identification tasks. This characterizes tasks seen in the field of face recognition, such as face identification and face verification, where people must be classified correctly with different facial expressions, lighting conditions, accessories, and hairstyles given one or a few template photos. ![]() One-shot learning is a classification task where one, or a few, examples are used to classify many new examples in the future.
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