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Enabling Brain Typing Via LSTM Recurrent Neural Network // GP // Dr. Ahmed Farouk (2018 - 2019) (Record no. 25095)

MARC details
000 -LEADER
fixed length control field 02543nam a22002177a 4500
003 - CONTROL NUMBER IDENTIFIER
control field OSt
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20190827083910.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 190827b ||||| |||| 00| 0 eng d
040 ## - CATALOGING SOURCE
Transcribing agency MSA
082 ## - DEWEY DECIMAL CLASSIFICATION NUMBER
Classification number 005
100 ## - MAIN ENTRY--PERSONAL NAME
Relator code Michael Maged Samir 163047
245 ## - TITLE STATEMENT
Title Enabling Brain Typing Via LSTM Recurrent Neural Network // GP // Dr. Ahmed Farouk (2018 - 2019)
260 ## - PUBLICATION, DISTRIBUTION, ETC.
Place of publication, distribution, etc. GIZA
Name of publisher, distributor, etc. MSA
Date of publication, distribution, etc. 2019
300 ## - PHYSICAL DESCRIPTION
Extent 76 P.
440 ## - SERIES STATEMENT/ADDED ENTRY--TITLE
Title COMPUTER SCIENCES DISTINGUISHED PROJECTS 2019
500 ## - GENERAL NOTE
General note Computer Science
520 ## - SUMMARY, ETC.
Summary, etc. In our ever-changing world, no one can survive or prosper in isolation. According to<br/>UNICEF, 30 per cent of street youths are disabled. Moreover, youth and new generations are of<br/>utmost importance in our modern world for a better future. It is sad to say that in our world, there<br/>are physically impaired people who are deprived from the very basic means of communication.<br/>Thus, sharing information in a bidirectional flow acts as a building block for constructive<br/>communication. Here comes the technology that saves those helpless people from this prison of<br/>not communication which is Brain-Computer Interface (BCI). As it is one of the most emerging<br/>technologies in the past 10 years. The project aims to make a BCI application that reads the<br/>human brain signals from an EEG device that then classifies these signals to commands that write<br/>the wanted text.<br/>By using deep learning the application will be able to classify these received signals and make<br/>use of these classes to be converted into commands to write the specified text. This state-of-the-<br/>art field can lend a helping hand and enable those who are physically disabled to be able to<br/>communicate better. The project is consisting of 2 phases. Phase one: which the user wears the<br/>EEG headset and by collecting data to feed it to the RNN model that will later train on these data<br/>for better analysis of the signals. Phase two: where the model have trained on this person data and<br/>able to classify his signals, all he will do is to imagine doing 1 of the 5 commands which are:<br/>moving right hand, moving left hand, moving legs, closing eye, moving both hands. Furthermore,<br/>this will help him to choose the specified letter to write the wanted word. By developing a high<br/>accuracy deep learning model this will help the humanity to have much brighter future.
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Brain Typing
Form subdivision LSTM
General subdivision Recurrent Neural Network
856 ## - ELECTRONIC LOCATION AND ACCESS
Uniform Resource Identifier <a href="https://drive.google.com/drive/folders/1_qAYz_awFncVRndyLCoKdmZtjHVWCu64">https://drive.google.com/drive/folders/1_qAYz_awFncVRndyLCoKdmZtjHVWCu64</a>
Public note FULL TEXT HERE
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Source of classification or shelving scheme Dewey Decimal Classification
Koha item type Distinguished Graduation Projects
Holdings
Withdrawn status Lost status Source of classification or shelving scheme Damaged status Not for loan Home library Current library Shelving location Date acquired Total Checkouts Full call number Barcode Date last seen Price effective from Koha item type
    Dewey Decimal Classification     Centeral Library Centeral Library Soft Copy located on library Cataloge 27.08.2019   GP293CS2019 82123 27.08.2019 27.08.2019 Distinguished Graduation Projects