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Computer Vision, as a part of Object Detection within Deep Learning and Artificial Intelligence, focuses on enabling computers to interpret and understand visual data from the world, much like humans do. It involves designing algorithms and models that can analyze images and videos, identify objects and their properties, and make predictions or decisions based on that analysis. Computer Vision builds upon Object Detection techniques such as Convolutional Neural Networks (CNNs) to extract features from visual data, recognize patterns, and make sense of the content in an image or video. In this context, Computer Vision can be thought of as the next level of abstraction after Object Detection. It seeks to understand not just what objects are present but also how they interact with each other, their attributes, and the overall scene layout. Computer Vision is a crucial component of many advanced technology applications, including autonomous vehicles, facial recognition systems, medical imaging analysis, and augmented reality. By providing computers with the ability to interpret visual data, Computer Vision helps advance Artificial Intelligence and Deep Learning technologies toward more sophisticated and human-like capabilities.