Convolutional neural networks

Concept and definition

Convolutional neural networks

What is Convolutional neural networks?

Convolutional neural networks (CNNs) use numerous identical replicas of the same network and each layer specializes in one task, the result of which is used in the next layer to solve complex problems.

The advantage of this is that it allows a network to learn a neuron once and use it in numerous places, simplifying the model learning process and thus reducing error. This has made CNNs especially useful in the field of object recognition and image labeling.
CNNs learn increasingly complex and abstract representations. Object recognition in CNNs can start with raw pixel data and learn very specific features, such as edges, basic and complex shapes, patterns and textures.

« Back to glossary

Do you want to get in touch?

CDRs contain data that a telecommunications company collects about phone calls, such as time and length of call. This data can be used in analytical applications.
Fill the form
Share:
Sales KPIs. What they are and which are the best

Achieving business goals and tracking success is an important aspect of improving any business. In sales, measuring the progress of [...]

Read More »
What is Artificial Intelligence doing today for the financial sector?

The Official Chamber of Commerce of Seville, in collaboration with the Spanish Institute of Financial Analysts (IEAF), offered last March 16th [...]

Read More »
12 Sectors with the greatest potential for entrepreneurship

Business opportunities are everywhere and many times we do not know which are the sectors with the greatest potential for entrepreneurship.

Read More »
Why Machine Learning (ML) is so popular in the 21st Century

The term artificial intelligence (AI) is nowadays, but it was invented in 1956 by John McCarthy, Marvin Minsky and Claude Shannon in the famous [...]

Read More »
See more entries
© Gamco 2021, All Rights Reserved - Legal notice - Privacy - Cookies