Understanding Convolutional Neural Networks

Understanding Convolutional Neural Networks

  • September 14, 2019
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Understanding Convolutional Neural Networks

A Convolutional Neural Network (CNN) is a class of deep, feed-forward artificial neural networks most commonly applied to analyzing visual imagery. The architecture of these networks was loosely inspired by biological neurons that communicate with each other and generate outputs dependent on the inputs. Though work on CNNs started in the early 1980s, they only became popular with recent technology advancements and computational capabilities that allow the processing of large amounts of data and the training of sophisticated algorithms in a reasonable amount of time.

Some of the applications of CNNs include AI-based virtual assistant, automatic photo tagging, video labeling, and self-driving cars. This blog assumes that you have a basic knowledge of neural networks. You can also check out Introduction to convolutional neural networks, which covers everything you need to know for this post.

Source: cloudera.com

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