As few as 10 labelled training images can be enough for image classification with extreme accuracy. As example, say an AI is trained this way with ten images each of elephants, tigers and bears.

Applications of few-shot learning techniques. One application of few-shot learning techniques is in healthcare, where medical images with their diagnoses can be used to develop a classification model.

Methods in Few-Shot Learning. There are several approaches employed in few-shot learning, each with its own strengths and applications. Here are a few prominent methods: ...