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    Language Translator: Google  Translate  uses  Natural  Language   EXAMPLES OF COMPUTER VISION
     Processing (NLP) and sequence-to-sequence modelling to translate   Here are some examples of computer vision:
     text accurately between languages. Previously, it relied on Statistical     Face recognition: Computer vision is used in security systems to
     Machine Translation (SMT), which was less accurate and based on   recognise faces and allow access to certain places or devices, such
     patterns in large translated texts.
                        as unlocking smartphones or granting entry to buildings.

       Grammar  Checkers: Grammar  and  spell checkers  are essential
     tools  for professional  writing.  They correct  mistakes,  suggest      Image search: Computer vision is used in search engines like Google
     synonyms  and improve  readability  using Natural Language   Images, allowing users to search for images based on their content. The

     Processing (NLP). These tools are widely used in offices, schools and   system analyses visual features like colour, shape and texture to find
     content creation.                         similar pictures, making image search more intuitive.

                         Medical imaging: Computer vision helps doctors analyse X-rays, CT
                        scans and MRIs to detect medical conditions like tumours, fractures
       Email Management: Emails are a key communication method.   or abnormalities, making diagnostics faster and more accurate.
     Email services use Natural Language Processing (NLP) and text
     classification to automatically sort messages into categories like
     primary, social and promotions, helping manage unwanted emails.    Autonomous  vehicles: Self-driving cars rely on computer  vision  to
                                               understand their surroundings. This includes detecting objects like traffic
                                               lights, pedestrians, other vehicles and road conditions, allowing the car
                                               to navigate safely without human intervention.

     COMPUTER VISION     Optical Character Recognition (OCR): OCR uses computer vision to
                        extract  text  from scanned  documents,  images  or even handwritten              OCR
     Computer Vision is a field of AI that enables machines to see and understand images, objects and   notes, enabling users to edit or search the text digitally. This technology
     actions, similar to human vision. Using cameras, sensors and smart programs, it turns images into   is used in applications like Google Docs and Adobe Acrobat.
     data for machines to process, making machines smarter by giving them sight. This technology is
     constantly evolving, enhancing the capabilities of machines in various industries.            21 st   #Initiative
                          INTERDISCIPLINARY LEARNING                                              Century   #Critical Thinking
                                                                                                   Skills
     Human Vision
                       Surf the Internet and research how computer vision is applied in agriculture to monitor crops and
                       predict harvest times. Explain  how this technology  helps farmers
     Dog                                                                                      social studies
                       improve crop yields and manage their fields more efficiently.

     Input  Eye  Brain  Output

                      RAPID RECALL                            Tick ( ) if you know this.
     Computer Vision
                         1.  NLP helps bridge the gap between human communication and computer
                            understanding.
     Dog
                         2.  Computer vision enables machines to understand images, objects and actions,
                            mimicking human vision.
     Input  Sensing device  Interpreting device  Output

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                                                                                                        Domains of AI

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