Research on generative sign language using neural networks
This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2021.
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| Jazyk: | English |
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Brac University
2021
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| On-line přístup: | http://hdl.handle.net/10361/14969 |
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10361-14969 |
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10361-149692022-01-26T10:15:49Z Research on generative sign language using neural networks Selim, Bushra Binte Iqbal, Maliha Shahriar, Asif Faria, Fauzia Mostafa, Rafid Mostakim, Moin Shakil, Arif Alam, Md. Golam Rabiul Department of Computer Science and Engineering, Brac University Sign Language Generation Neural Network Neural Networks for Sign Language Generative Sign CNN Inceptionv3 Sign language. This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2021. Cataloged from PDF version of thesis. Includes bibliographical references (pages 41-44). Sign gesture, which is one type of non-audible specialized strategy is the medium to correspond with individuals having auditory and talking incompetency. There are numerous computerized methods of creating gesture-based communication to provide aid among the hearing impaired. Particularly, for Bengali sign dialect, quite a few measures have been taken for generation of automated Bangla sign gestures. With an authentic dataset and approach, an apparent communication mode to assist this non-privileged community can be attained. Our method proposes a convolutional neural network (CNN) to derive a picture of the appropriate sign gesture of a particular Bangla alphabet. After our examinations and multiple experiments, we have come up with the simplest and most striking methodology to perform the mentioned task. Our model worked promptly and provided remarkable accuracy. Needless to mention that, communication through gestures aided by artificial means is another corner that needs to be explored more. Henceforth, our work can have an added value to this ongoing inspection. Bushra Binte Selim Maliha Iqbal Asif Shahriar Fauzia Faria Rafid Mostafa B. Computer Science 2021-09-04T10:14:00Z 2021-09-04T10:14:00Z 2021 2021 Thesis ID 21141052 ID 21141050 ID 16301040 ID 17141007 ID 16101069 http://hdl.handle.net/10361/14969 en Brac University theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. 44 pages application/pdf Brac University |
| institution |
Brac University |
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Institutional Repository |
| language |
English |
| topic |
Sign Language Generation Neural Network Neural Networks for Sign Language Generative Sign CNN Inceptionv3 Sign language. |
| spellingShingle |
Sign Language Generation Neural Network Neural Networks for Sign Language Generative Sign CNN Inceptionv3 Sign language. Selim, Bushra Binte Iqbal, Maliha Shahriar, Asif Faria, Fauzia Mostafa, Rafid Research on generative sign language using neural networks |
| description |
This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2021. |
| author2 |
Mostakim, Moin |
| author_facet |
Mostakim, Moin Selim, Bushra Binte Iqbal, Maliha Shahriar, Asif Faria, Fauzia Mostafa, Rafid |
| format |
Thesis |
| author |
Selim, Bushra Binte Iqbal, Maliha Shahriar, Asif Faria, Fauzia Mostafa, Rafid |
| author_sort |
Selim, Bushra Binte |
| title |
Research on generative sign language using neural networks |
| title_short |
Research on generative sign language using neural networks |
| title_full |
Research on generative sign language using neural networks |
| title_fullStr |
Research on generative sign language using neural networks |
| title_full_unstemmed |
Research on generative sign language using neural networks |
| title_sort |
research on generative sign language using neural networks |
| publisher |
Brac University |
| publishDate |
2021 |
| url |
http://hdl.handle.net/10361/14969 |
| work_keys_str_mv |
AT selimbushrabinte researchongenerativesignlanguageusingneuralnetworks AT iqbalmaliha researchongenerativesignlanguageusingneuralnetworks AT shahriarasif researchongenerativesignlanguageusingneuralnetworks AT fariafauzia researchongenerativesignlanguageusingneuralnetworks AT mostafarafid researchongenerativesignlanguageusingneuralnetworks |
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1814308323878502400 |