Artificial neural networks (ANNs) are models based on the neural networks in the human brain that react and adapt to information, learning to make decisions based off that information, in theory, the same way a human would. ANNs require a data pool as a baseline for learning. The more data available, the more connections a neural network can make and the more it can learn. As an ANN learns, it can consistently give accurate outputs based on the solution a user is seeking. Deep neural networks (DNNs) are ANNs that have hidden layers between input and output. Developers use DNNs when building an intelligent application with deep learning functionality. Artificial neural networks are the basis for other deep learning algorithms, such asimage recognition,natural language processing, andvoice recognition, among others.
To qualify for inclusion in the Artificial Neural Networks category, a product must: