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Convolutional Neural Network (CNN) in Machine Learning

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  • Difficulty Level : Expert
  • Last Updated : 28 Dec, 2020
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In this article, we are going to discuss convolutional neural network(CNN) in machine learning in detail.

Convolutional Neural Network(CNN) :

  • A convolutional neural network, or CNN, is a deep learning neural network sketched for processing structured arrays of data such as portrayals.
  • CNN are very satisfactory at picking up on design in the input image, such as lines, gradients, circles, or even eyes and faces.
  • This characteristic that makes convolutional neural network so robust for computer vision.
  • CNN can run directly on a underdone image and do not need any preprocessing.
  • A convolutional neural network is a feed forward neural network, seldom with up to 20.
  • The strength of a convolutional neural network comes from a particular kind of layer called the convolutional layer.
  • CNN contains many convolutional layers assembled on top of each other, each one competent of recognizing more sophisticated shapes.
  • With three or four convolutional layers it is viable to recognize handwritten digits and with 25 layers it is possible to differentiate human faces.
  • The agenda for this sphere is to activate machines to view the world as humans do, perceive it in a alike fashion and even use the knowledge for a multitude of duty such as image and video recognition, image inspection and classification, media recreation, recommendation systems, natural language processing, etc.

Convolutional Neural Network Design :

  • The construction of a convolutional neural network is a multi-layered feed-forward neural network, made by assembling many unseen layers on top of each other in a particular order.
  • It is the sequential design that give permission to CNN to learn hierarchical attributes.
  • In CNN, some of them followed by grouping layers and hidden layers are typically convolutional layers followed by activation layers.
  • The pre-processing needed in a ConvNet is kindred to that of the related pattern of neurons in the human brain and was motivated by the organization of the Visual Cortex.

Case Study of CNN for Diabetic retinopathy :

  • Diabetic retinopathy also known as diabetic eye disease, is a medical state in which destruction occurs to the retina due to diabetes mellitus, It is a major cause of blindness in advance countries.
  • Diabetic retinopathy influence up to 80 percent of those who have had diabetes for 20 years or more.
  • The overlong a person has diabetes, the higher his or her chances of growing diabetic retinopathy.
  • It is also the main cause of blindness in people of age group 20-64.
  • Diabetic retinopathy is the outcome of destruction to the small blood vessels and neurons of the retina.
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