What type of AI systems are designed to identify and categorize patterns or objects in data, such as facial recognition systems?

Recognition systems are specifically designed to identify and categorize patterns or objects within data, such as images, sounds, or other inputs. In the case of facial recognition systems, these AI systems utilize complex algorithms to analyze facial features, compare them against a database, and ultimately categorize or recognize individual faces. This capability is key to applications ranging from security and surveillance to personalized user experiences.

While classification systems share some similarities with recognition systems, they generally focus on assigning a label to an entire dataset rather than identifying specific patterns within complex data structures, like those used in facial recognition. Regression systems deal with predicting continuous values rather than identifying or classifying data patterns, making them inappropriate for tasks like facial recognition. Detection systems often involve the identification of the presence or absence of an object within data but do not focus on the categorization aspect as recognition systems do. Therefore, recognition systems are most accurately defined as those that fulfill the needs outlined in the question.