These networks with a large number of artificial neurons and different layers of weights process the inputs and produce the desired output. By training an artificial neural network, they can recognize patterns and features associated with different categories.
The most pervasive approaches used in computer vision
It is deep neural networks. These networks, with a deep structure and a high number of layers, have the superior ability to recognize patterns and complex features. Deep neural networks are usually built with several hidden layers and each layer contains a set of programmed neurons.
Eventually
By learning these networks using large and diverse data sets, the networks can be able to recognize and identify objects, group categories and interpret visual scenes. Also, computer vision has a very important role in the field of autonomous driving. By using computer vision and deep neural networks, facilities such as recognition and marking of cars, recognition of augmented reality (Augmented Reality), recognition of pedestrians who intend to cross the street, and other tasks related to self-driving are performed.