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ISSN Approved Journal No: 2320-2882 | Impact factor: 7.97 | ESTD Year: 2013
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Published Paper Details:
Paper Title
Traffic Sign Recognition Using Convolutional Neural Network
Authors
Dushyanth Cheepilli, Devi Prasanna Pilla
Keywords
Traffic Sign Recognition, CNN, Deep CNN, Data Set, Image Processing, Pooling Layers, Deployment
Abstract
Traffic sign detection and recognition have gained importance with advances in image processing due to the benefits that such a system may provide. The recent developments and interest in self-driving cars have also increased the interest in this field. Automatic detection and recognition of traffic signs is very important and could potentially be used for driver assistance to reduce accidents and eventually in driverless automobiles. There are many sign boards on roads that people are unaware of. They might have seen traffic or road signs all the time but don't understand what those signs are indicating. Our Traffic Sign Recognition
System detects and recognizes road signs or traffic signs from an image and video. It will also recognize signs in real-time using CNN. Here, Deep Convolutional Neural Network (CNN) is used to develop Autonomous Traffic or Road Sign
IJCRT's Publication Details
Unique Identification Number - IJCRT2407408
Paper ID - 265726
Page Number(s) - d468-d478
Pubished in - Volume 12 | Issue 7 | July 2024
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Publisher Name - IJCRT | www.ijcrt.org | ISSN : 2320-2882
E-ISSN Number - 2320-2882
Cite this article
Dushyanth Cheepilli, Devi Prasanna Pilla, "Traffic Sign Recognition Using Convolutional Neural Network", International Journal of Creative Research Thoughts (IJCRT), ISSN:2320-2882, Volume.12, Issue 7, pp.d468-d478, July 2024, Available at :http://www.ijcrt.org/papers/IJCRT2407408.pdf
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Volume 14 | Issue 2
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February 2026
Volume 14 | Issue 2
Last Date :
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Submit Manuscript Online Impact Factor: 7.97 Review Results : Within 02-03 Days Paper Publication : Within 02-03 Days
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ISSN: 2320-2882 Impact Factor: 7.97 and ISSN APPROVED Journal Starting Year (ESTD) : 2013
ISSN and 7.97 Impact Factor Details
ISSN: 2320-2882 Impact Factor: 7.97 and ISSN APPROVED Journal Starting Year (ESTD) : 2013
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