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Smart Drive Safe: Harnessing CNN for Enhanced Traffic Sign Recognition and Voice Alerts
Traffic signs secure their safety on the roads and the protection of others around them; everyone must be aware of traffic signs and other aspects of road safety. Traffic sign detection is a highly relevant computer vision problem that forms the basis of numerous applications in sectors like the aut...
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creator | Priya, D. Divya Chinnasamy, P. Ayyasamy, Ramesh Kumar Kiran, Ajmeera A Jalil, Norazira Binti Sangodiah, Anbuselvan |
description | Traffic signs secure their safety on the roads and the protection of others around them; everyone must be aware of traffic signs and other aspects of road safety. Traffic sign detection is a highly relevant computer vision problem that forms the basis of numerous applications in sectors like the automotive industry. Between classes, traffic signs differ widely in terms of colour, shape, and the use of pictograms or text. The project's classification of traffic signs in an image into various categories is based on a deep neural network model. IoT devices that capture traffic signs and notify users of them are used to build a model. |
doi_str_mv | 10.1109/ICESC60852.2024.10690129 |
format | conference_proceeding |
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Divya</creatorcontrib><creatorcontrib>Chinnasamy, P.</creatorcontrib><creatorcontrib>Ayyasamy, Ramesh Kumar</creatorcontrib><creatorcontrib>Kiran, Ajmeera</creatorcontrib><creatorcontrib>A Jalil, Norazira Binti</creatorcontrib><creatorcontrib>Sangodiah, Anbuselvan</creatorcontrib><collection>IEEE Electronic Library (IEL) Conference Proceedings</collection><collection>IEEE Proceedings Order Plan All Online (POP All Online) 1998-present by volume</collection><collection>IEEE Xplore All Conference Proceedings</collection><collection>IEEE Electronic Library Online</collection><collection>IEEE Proceedings Order Plans (POP All) 1998-Present</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Priya, D. 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Between classes, traffic signs differ widely in terms of colour, shape, and the use of pictograms or text. The project's classification of traffic signs in an image into various categories is based on a deep neural network model. IoT devices that capture traffic signs and notify users of them are used to build a model.</abstract><pub>IEEE</pub><doi>10.1109/ICESC60852.2024.10690129</doi></addata></record> |
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identifier | EISSN: 2996-5357 |
ispartof | 2024 5th International Conference on Electronics and Sustainable Communication Systems (ICESC), 2024, p.1915-1920 |
issn | 2996-5357 |
language | eng |
recordid | cdi_ieee_primary_10690129 |
source | IEEE Xplore All Conference Series |
subjects | Cameras Convolutional neural network datasets Hardware Image color analysis Industries Internet of Things object detection Protection Real-time systems Road safety Shape Speech recognition Traffic Sign Recognition Traffic signs Voice alert |
title | Smart Drive Safe: Harnessing CNN for Enhanced Traffic Sign Recognition and Voice Alerts |
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