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Page 24 - Ai Robogenius
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    STEP - 2    Image Processing: The computer breaks the image into tiny dots called pixels. Then
                                   it uses algorithms (smart instructions) to detect patterns and features in the image.

                       STEP - 3    Object Recognition: The system tries to identify what’s in the image—like a face,
                                   object, shape or even text—by comparing it with what it has learned before (pre
                                   trained data).
                       STEP - 4    Decision-making: Based on what it sees, the computer takes action. This could mean
                                   moving a robot, raising an alarm, stopping a machine or making an independent
                                   decision. For example,

                                     At an international airport, a tech company is developing a facial recognition system
                                   to enhance passenger security and speed up the check-in process. The system is
                                   built in three main stages.

                                      Training                      Analysis                   Interpretation

                                  System analysis new         System analysis new          System interpretation
                                 images, identifying key       images, it identifies      analysis data and makes
                                 features and patterns            key patterns                   a decision

                                  In the first stage, the developers upload a large number of face images into the system.
                                These images include people of different ages, backgrounds and expressions. This helps
                                the system learn the key features of a human face, such as eye position, nose shape and
                                facial structure. This stage is known as training, where the system learns from a large
                                dataset to recognise different types of faces.
                                  In the second stage, the system begins to analyse the new images it receives. It studies
                                important patterns and compares them with what it learned during training. It looks
                                for specific details that make each face unique, such as the distance between eyes or
                                the shape of the jawline. This stage is called analysis, where the system identifies useful
                                features from the input data.

                                  In the final stage, the system uses its analysis to decide who the person is. When a new
                                traveller stands in front of the camera, the system compares the live image with its
                                memory and identifies the person. This stage is called interpretation, where the system
                                makes a decision based on the patterns it has recognised.

                                     AI RoboGenius - VI
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