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Computer vision encompasses the development of algorithms and models that enable computers to interpret, analyze, and understand visual information from the world, much like humans do through their eyes. It combines principles from electronics, computer science, mathematics, and artificial intelligence to process, extract, and learn patterns from digital images and videos. This field has applications in various domains such as robotics, medical imaging, autonomous vehicles, facial recognition, and augmented reality. By leveraging machine learning techniques, computer vision systems can improve their accuracy and capabilities over time, unlocking new possibilities for automation and decision-making. Ultimately, computer vision aims to bridge the gap between the digital and physical worlds by enabling machines to perceive and understand visual data with unprecedented precision and insight.