Artificial Neural Networks
What are artificial neural networks?
Artificial neural networks (NN) are inspired by the structure and functioning of the human brain, in which nerve cells are interconnected via synapses. Similar to the learning process in the brain, in which frequently used signal paths are strengthened and rarely used paths are weakened, data can be processed in NN and controlled by weightings of the signal paths.
How do artificial neural networks learn?
Before an NN is ready for use, it must be trained. This can be done, for example, using already annotated data. To teach an NN to identify bone fractures in X-ray images, one presents X-ray images of bones to the network and simultaneously indicates whether a fracture is present or not. In this way, the NN learns to recognize bone fractures in X-ray images.
Where do artificial neural networks find application?
NN are used in numerous fields. In medicine, they support the diagnosis of diseases by analyzing images. In the entertainment sector, they are used to recognize faces in photos or provide music recommendations based on listening habits. In the field of autonomous driving, they help vehicles interpret their surroundings and navigate safely.
Despite careful control of the content, we assume no liability for the content of external links. The operators of the linked pages are solely responsible for their content.