Convolutional Neural Network in classifying scanned documents


Internship Report, 2016

33 Pages


Excerpt


Contents

1 Introduction
1.1 Context
1.1.1 About ICTLab
1.1.2 ARCHIVES project
1.1.3 Internship context
1.2 Report organization

2 State of the art
2.1 Artificial intelligence & machine learning
2.2 Artificial neural network (ANN)
2.2.1 History
2.2.2 Regular neural network
2.2.3 Convolutional neural network (LeNet)
2.2.4 Training and evaluating

3 Contribution
3.1 Data creation and augmentation
3.1.1 ARCHIVES dataset
3.1.2 Creating data
3.1.3 Augmenting the data
3.1.4 Summary and Result
3.2 Constructing the convolution neural network (LeNet) .
3.2.1 The model
3.2.2 Preparing data
3.2.3 Training
3.2.4 Validation and testing
3.3 Developing the network

4 Results
4.1 The basic network
4.1.1 Testing on the dataset
4.1.2 Testing on real images
4.2 The network modifications
4.2.1 Fully connected layer
4.2.2 Convolutional layers
4.3 The new network

5 Conclusion

A Transfer functions

Excerpt out of 33 pages

Details

Title
Convolutional Neural Network in classifying scanned documents
College
University of Science and Technology of Hanoi
Course
Internship
Author
Year
2016
Pages
33
Catalog Number
V349852
ISBN (eBook)
9783668371675
ISBN (Book)
9783668371682
File size
3330 KB
Language
English
Keywords
machine learning, deep learning, classification, internship, computer science, neural network, convolutional neural network, leNet
Quote paper
Tai Doan (Author), 2016, Convolutional Neural Network in classifying scanned documents, Munich, GRIN Verlag, https://www.grin.com/document/349852

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