A neural network is a network or circuit of neurons. The neural network has layers of units where each layer takes some value from the previous layer. That way, systems that are based on neural network can compute inputs to get the needed output. The same way neurons pass signals around the brain, and values are passed from one unit in an artificial neural network to another to perform the required computation and get new value as output. The united are layers, forming a system that starts from the layers used for imputing to layer that is used to provide the output

1. CHARACTER / DIGIT RECOGITION
BASED ON
DEEP NEURAL NETWORKS
By,
G. Yashwanth
(19R11A05L8)

2. Contents:
• Introduction to deep neural networks.
• Dataset
• Work flow
• Classification
• Applications
• Advantages
• Conclusion

3. INTRODUCTION
TO
DEEP NEURAL NETWORK

4. INTRODUCTION
• A neural network is a network or circuit of neurons.
• The neural network has layers of units where each layer takes some
value from the previous layer.
• That way, systems that are based on neural network can
compute inputs to get the needed output.
• The same way neurons pass signals around the brain, and values
are passed from one unit in an artificial neural network to another
to perform the required computation and get new value as output.
• The united are layers, forming a system that starts from the layers
used for imputing to layer that is used to provide the output.

5. Basic Structure Of Neural Networks:

6. Dataset:
• The dataset is obtained from “Modified National Institute of
Standards and Technology” – MNIST
• It contains both characters and Digits Data sets.

7. Work Flow:
MNIST DATA SET
Training
images
Testing
images
Input layer of DNN
Training
of DNN
model
Predictions using trained model

8. Classification:

9. Working:
Input Layer
Hidden layers
Output layer
Forward Propagation
Backward propagation
Accuracy (0.9)

10. Applications:
• Military
• Medical Field
• Aerospace
• Automotive

11. Advantages:
• When an element of the neural network fails, it can
continue by their parallel nature.
• Ability to train machine.
• The ability to work with insufficient knowledge.

12. Conclusion:
So, we have seen Character and Digit Recognition Based Deep
Neural Network and approached our solution in three steps i.e.:
• Image Identification
• Digit Recognition
• Character Recognition