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Computer vision techniques refer to methods and algorithms used to enable computers to interpret and understand visual data from the real world. These techniques involve processing, analyzing, and extracting information from images and videos to make sense of the visual content. They encompass a wide range of processes such as image recognition, object detection, image segmentation, facial recognition, and motion tracking. Computer vision techniques often rely on machine learning and deep learning algorithms to train models for accurate and efficient interpretation of visual data. These techniques are widely used in various applications including autonomous vehicles, surveillance systems, medical imaging, augmented reality, and robotics.