In the present-day context, security has emerged as a matter of utmost significance, particularly for individuals and businesses striving to safeguard their assets and people. While conventional video surveillance systems have long been relied upon, they come with inherent limitations.
Computer vision technology of today is powered by deep learning algorithms that use a special kind of neural networks, called convolutional neural network (CNN), to make sense of images. These neural networks are trained using thousands of sample images which helps the algorithm understand and break down everything thats contained in an image. These neural networks scan images pixel by pixel, to identify patterns and memorize them. It also memorizes the ideal output that it should provide for each input image (in case of supervised learning) or classifies components of images by scanning characteristics such as contours and colors. This memory is then used by the systems as the reference while scanning more images. And with every iteration, the AI system becomes better at providing the right output.