GR Semicolon EN

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dc.contributor.author
Liampas, Christos
en
dc.date.accessioned
2021-09-03T08:23:43Z
dc.date.available
2021-09-03T08:23:43Z
dc.date.issued
2021-09-03
dc.identifier.uri
https://repository.ihu.edu.gr//xmlui/handle/11544/29763
dc.rights
Default License
dc.subject
TensorFlow
en
dc.subject
Neural networks
en
dc.subject
Android
en
dc.subject
Camera
en
dc.subject
ESP32
en
dc.title
TensorFlow Android Application for Character Recognition using Mobile Cameras
en
heal.type
masterThesis
en_US
heal.creatorID.email
csliampas@gmail.com
heal.dateAvailable
2021-06-21
heal.language
en
en_US
heal.access
free
en_US
heal.license
http://creativecommons.org/licenses/by-nc/4.0
en_US
heal.recordProvider
School of Science and Technology, MSc in Mobile and Web Computing
en_US
heal.publicationDate
2021-06-21
heal.abstract
This dissertation was written as part of the MSc in Mobile & Web Computing at the International Hellenic University. The purpose of this paper is the understanding of the deep learning theory, including terms like Neural Networks, activation functions, loss functions, optimizers, overfitting, data augmentation, and more, having as a final objective the development of a TensorFlow (TF) model that can recognize characters of the English alphabet. This model is then converted into a compatible lite version in order to be imported into an Android application that was developed for this thesis. The user can then capture images through the app’s interface by using the phone’s camera, or by using a custom-made and programmed smart IoT remote camera (R-CAM) through Bluetooth, to feed into the TensorFlow model and present a prediction on the phone’s screen. The thesis was completed successfully within the predetermined deadline. Of course, there is always room for improvement as determined in the last chapter of this thesis.
en
heal.advisorName
Akritidis, Leonidas
en
heal.committeeMemberName
Akritidis, Leonidas
en
heal.committeeMemberName
Politis, Anastasios
en
heal.committeeMemberName
Rantos, Konstantinos
en
heal.academicPublisher
IHU
en
heal.academicPublisherID
ihu
en_US


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