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INTERNATIONAL JOURNAL OF CREATIVE RESEARCH THOUGHTS - IJCRT (IJCRT.ORG)
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ISSN Approved Journal No: 2320-2882 | Impact factor: 7.97 | ESTD Year: 2013
Call For Paper - Volume 12 | Issue 7 | Month- July 2024
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Paper Title
Efficient Roadway Management Through AI-Powered Damage Detection And Lane Detection
Authors
Krishnamaneni Archana, Kallepu Saketh Reddy, Chilaka Komali, Sree Vidhya Maddineni, Talathoti Ramya sri
Keywords
YOLOv8, Canny edge detection, roadway management, AI-powered damage detection, lane detection, self-driving cars, machine learning, computer vision, real-time detection, transportation safety.
Abstract
The objective of this project is to improve roadway management for autonomous vehicles by implementing AI-powered damage detection and lane detection systems. The primary focus is to develop algorithms that can accurately identify road damage and detect lane markings in real-time. By leveraging machine learning and computer vision techniques, this system aims to enhance safety and efficiency on roadways. The damage detection component will help self-driving cars navigate around obstacles and hazards effectively, while the lane detection feature ensures precise vehicle positioning within designated lanes. Overall, this integrated approach aims to improve the capabilities of autonomous vehicles, contributing to safer and more reliable transportation systems.
IJCRT's Publication Details
Unique Identification Number - IJCRT24A3108
Paper ID - 254221
Page Number(s) - j338-j343
Pubished in - Volume 12 | Issue 3 | March 2024
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Publisher Name - IJCRT | www.ijcrt.org | ISSN : 2320-2882
E-ISSN Number - 2320-2882
Cite this article
Krishnamaneni Archana, Kallepu Saketh Reddy, Chilaka Komali, Sree Vidhya Maddineni, Talathoti Ramya sri, "Efficient Roadway Management Through AI-Powered Damage Detection And Lane Detection", International Journal of Creative Research Thoughts (IJCRT), ISSN:2320-2882, Volume.12, Issue 3, pp.j338-j343, March 2024, Available at :http://www.ijcrt.org/papers/IJCRT24A3108.pdf
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Volume 12 | Issue 7
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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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