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 that’s 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.
Web Camera Pro application uses data vision theory to identify objects within video, search through catalogues of images, and extract information out of images.
Object detection deals with detecting instances of semantic objects of a certain class (such as a dog, a human, or a car.) in digital images and videos.
Web Camera Pro Video Surveillance
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