In specific tasks, computer vision can perform better than human vision, particularly when speed, accuracy, or consistency is critical. For example, algorithms can detect patterns in large datasets or images much faster than humans and are not prone to fatigue.
In applications like medical imaging, computer vision models can identify minute abnormalities that may be overlooked by the human eye. Similarly, autonomous vehicles use vision systems to process vast amounts of visual data in real time, making decisions faster than a human driver could.
However, human vision still outperforms computer vision in general tasks requiring contextual understanding, creativity, or adaptability. While computer vision excels in narrow domains, it lacks the comprehensive reasoning capabilities of human perception.