Page 311 - AI Computer 10

of neurons which are either organic or artificial in nature. It is a neural network which serves as a powerful
technology in many computer vision applications. Before learning convolutional neural networks in detail, you
should be acquainted with the knowledge about neural networks and the names of different layers used in a
given neural network.

Pop Quiz Quiz
Pop
Label the various layers of the neural network shown in the given image.

________ ________ ________ ________

Convolution Neural Network

As you learnt, a convolution is the simple application of a filter to an input image that gives us an enhanced
output image. CNNs or ConvNets, the acronym for Convolution Neural Network, refer to a category of neural
networks that have proven very effective in various areas like image recognition and classification. ConvNets
have been successful in identifying faces, objects, and traffic signs apart from powering vision in robots and
self-driving cars. CNNs are powerful deep learning algorithms that assign weights and biases to various aspects/
objects available in the input image. The weights in the network are initialized to small random numbers ranging
from-1.0 to 1.0, or -0.5 to 0.5. Each unit has a bias associated with it. The biases are similarly initialized to small
random numbers.
A Convolutional Neural Network (CNN) is a multilayer, feed-forward neural network that uses perceptrons for
supervised learning and data analysis. It is used mainly with visual data, such as image classification. These
networks are basically designed to process data through multiple layers of arrays. As you know, feature extraction
is an important part of AI systems which is being performed by the neural networks. The primary difference
between CNN and any other ordinary neural network is that CNN takes input as a two-dimensional array and
operates directly on the images rather than focusing on feature extraction. The various applications of CNNs are
as follows:

u Product Recommendation Engine: Product
Recommendation Engine is a field where image
classification and object recognition can be easily
carried out by CNNs. For example, Amazon uses
CNN image recognition for displaying suggestions
in the “you might also like” section. The basis of
the assumption is the user’s expressed behaviour.
The products themselves are matched on visual
criteria like black high heels for a black dress.

u Medical Image Classification: Nowadays, medical practitioners use
CNNs medical image classification to detect the various kinds of
anomalies in an X-ray or MRI as higher precision is not possible with
human vision.

177
177