The field of computer science known as "computer vision" investigates the capabilities of computers to see and understand moving images and still photographs. Understanding visual inputs, extracting complex information that may be used in other machine learning tasks, and presenting this information back to the user are all part of computer vision. Explain When applied to human recognition, how does the haarcascade classifier work?
The field of computer science known as "computer vision" investigates the capabilities of computers to see and understand moving images and still photographs. Understanding visual inputs, extracting complex information that may be used in other machine learning tasks, and presenting this information back to the user are all part of computer vision. Explain When applied to human recognition, how does the haarcascade classifier work?
Introduction
The Haar-like features are used in the Haar Cascade classifier, which is a machine learning-based object detection algorithm. The basic idea behind the Haar Cascade classifier is to create a cascade of classifiers, each of which focuses on detecting a particular feature of the object. For example, one classifier may be used to detect the edges of an object, while another classifier may be used to detect the eyes, nose, or mouth of a face.
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