History of Computer Vision
Last Updated 11/19/2025
Last Updated 11/19/2025
In the past, computers were only able to tell basic things: edges, lines, circles, and such. The thought of a computer distinguishing between an apple and orange with high accuracy was closer to science fiction than reality. In 2015, the algorithm as it was called at the time (now known as model) You Only Look Once (YOLO) was introduced, which revolutionized computer vision for solving the problem of object detection.
YOLO solved the problem of image objection and have accuracy rates of more than 99% alongside efficiency as only it required only one forward propagation to pass through the neural network to make predictions, rather than the previous proposed computer vision techniques that needed hundreds of forward propagation for only one image.
In the past, computers were only able to tell basic things: edges, lines, circles, and such. The thought of a computer distinguishing between an apple and orange with high accuracy was closer to science fiction than reality. In 2015, the algorithm as it was called at the time (now known as model) You Only Look Once (YOLO) was introduced, which revolutionized computer vision for solving the problem of object detection.
YOLO solved the problem of image objection and have accuracy rates of more than 99% alongside efficiency as only it required only one forward propagation to pass through the neural network to make predictions, rather than the previous proposed computer vision techniques that needed hundreds of forward propagation for only one image.
Research conducted in Computer Vision is conducted to assist humans in making decisions such as healthcare professionals in diagnosing human diseases such as tumors, faculty workers in predicting if equipment requires maintenance before it breaks, environmentalists in identifying species in the natural world, and more real life applications.