This document provides an overview of convolutional neural networks (CNNs). It defines CNNs as multiple layer feedforward neural networks used to analyze visual images by processing grid-like data. CNNs recognize images through a series of layers, including convolutional layers that apply filters to detect patterns, ReLU layers that apply an activation function, pooling layers that detect edges and corners, and fully connected layers that identify the image. CNNs are commonly used for applications like image classification, self-driving cars, activity prediction, video detection, and conversion applications.

1. Convolutional Neural
Networks
By
Vignesh
Suresh
FMIT20210

2. 1
2
4
5
How Image Recognition Works?
What is CNN ?
3 How CNN recognizes Images ?
CNN Layers
Applications of CNN
CONTENTS

3. HOW IMAGE RECOGNITION WORKS
Pikachu
Squirtle
Bulbasa
ur
The Machine uses the CNN (Convolutional Neural Network ) to recognize an image
Input Layer Hidden Layer Output Layer

4. WHAT TYPE OF NEURAL NETWORK IS CNN?
Single
Layer
Feed
Forwar
d
Multiple
Layer
Feed
Forward

5. WHAT IS CNN?
Pikachu
Squirtle
CNN is a multiple layer feed forward neural network used to analyze visual image by
processing data with grid like topology. A CNN is also called as ConvNet.
Input Layer Hidden Layer Output Layer

6. HOW CNN RECOGNIZES IMAGES?
1 0 0 1 1 0 0 1 1 0
0 1 1 0 1 1 0 1 1 0
1 0 0 1 0 0 0 1 0 1
0 1 1 1 0 1 0 1 0 1
1 0 0 1 0 0 0 1 1 0
1 1 1 1 0 1 1 0 1 0
0 0 0 1 0 0 1 0 0 1
1 0 1 1 0 1 1 0 0 1
0 0 0 1 0 0 1 0 1 0
1 0 0 1 0 1 1 0 1 0
Real Image of
Squirtle
Representation in the
form of array
Pixel representation
of 0 and 1’s
The Base of Convolutional Neural Network is Convolutional Operation.
Every image in CNN is represented as array of pixels values.

7. CONVOLUTIONAL OPERATION
A=[1,2,3,4,
5]
B=[1,2,3]
Matrix A and B
A *
B
A=[1,2,3,4,5
]
Multiply the
Arrays element
wise
Sum of
the
Product
[1,4,9
]
14
[2,6,12
]
20
[3,8,15
]
26
A* B = [14,20,26]
B=[1,2,3]

8. CNN LAYERS
CNN
Convolutional Layer
1
ReLU Layer
2
3
Pooling Layer
Fully Connected
Layer 4

9. CNN LAYERS
Pikachu
Input Layer Hidden Layer Output Layer
1 0 1
1 0 1
0 0 1
Input Layer Convolutional Layer
Input Layer accepts the
pixels of the image as
input in the form of arrays
Convolutional Layer uses
matrix filter, performs
convolutional operation
and detect patterns
ReLU Layer
ReLU Activation function
is applied to
Convolutional Layer for
getting a rectified map of
the image
Pooling Layer
Pooling Layer uses
multiple filters to detect
edges, corners , eyes etc.
Fully Connected
Layer
Fully Connected Layer is
the output layer that
identifies the image.

10. CNN APPLICATIONS
1 Self Driving Cars
2 Image Classification
3 Weather Predictions , Activity
Predictions
4 Detections in Videos
5 Conversion Applications