Convolutional Neural Network – In this article, we will explore our intuitive explanation of convolutional neural networks (CNN’s) on high level. CNN’s are inspired by the structure of the brain but our focus will not be on neural science in here as we do not specialise in any biological aspect. We are going artificial in this post.
Convolutional Neural Networks are a special kind of multi-layer neural networks.
What are Convolutional Neural Networks
Convolutional neural networks (CNN) – Might look or appears like magic to many but in reality, it’s just a simple science and mathematics only.
CNN’s are a class of Neural Networks that have proven very effective in areas of image recognition, processing and classification.
As per Wiki – In machine learning, a convolutional neural network (CNN, or ConvNet) is a class of deep, feed-forward artificial neural networks, most commonly applied to analysing visual imagery.
Artificial Intelligence solutions behind CNN’s amazingly transform how businesses and developers create user experiences and solve real-world problems. CNN’s are also known as application of neuroscience to machine learning. They employe mathematical operations known as “Convolution”; which is a specialised kind of linear operation.
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