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INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT International Peer Reviewed & Refereed Journals, Open Access Journal ISSN Approved Journal No: 2456-4184 | Impact factor: 8.76 | ESTD Year: 2016 Scholarly open access journals, Peer-reviewed, and Refereed Journals, Impact factor 8.76 (Calculate by google scholar and Semantic Scholar | AI-Powered Research Tool) , Multidisciplinary, Monthly, Indexing in all major database & Metadata, Citation Generator, Digital Object Identifier(DOI) |
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| Paper Title: | Novel Intelligent Lane Line Detection System using Neural Networks |
| Authors Name: | Niveditha Amarnath , Divya P S , A Aravindh Kumar |
| Download E-Certificate: | Download |
| Author Reg. ID: |
IJNRD_207915
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| Published Paper Id: | IJNRD2310393 |
| Published In: | Volume 8 Issue 10, October-2023 |
| DOI: | |
| Abstract: | The proposed system is a ground-breaking method for lane recognition and assistance through the combination of Artificial Intelligence (AI), OpenCV, and Convolutional Neural Networks (CNNs) in the aim of improving road safety and driving experiences. By combining predictive lane change assistance, the proposed system goes beyond traditional lane recognition techniques and combines driver and AI interactions. Our technology makes use of CNNs to not only recognize lanes but also predict probable lane changes, giving drivers timely notifications and recommendations. The critical requirement for safer driving habits in light of changing traffic situations serves as the motivating force for this research. When dealing with complicated circumstances including multi-lane roadways, metropolitan settings, and various illumination conditions, traditional lane identification systems sometimes fall short. The technology overlays recognized lanes on live video and enables smooth driver involvement through a user-friendly graphical interface. Another example of how AI might encourage cooperative driving practices is the incorporation of vehicle communication for cooperative lane change assistance. A safer and more organized driving environment is made possible by the system, which also significantly improves lane detection accuracy. The emphasis on the relevance of AI-augmented driving in the contemporary automotive scene and highlights the possibilities for integration with navigation and autonomous driving systems. |
| Keywords: | AI: Artificial Intelligence, CNN: Convolutional Neural Network, OpenCV, advanced driver-assistance system, lane detection and prediction |
| Cite Article: | "Novel Intelligent Lane Line Detection System using Neural Networks", International Journal of Novel Research and Development (www.ijnrd.org), ISSN:2456-4184, Vol.8, Issue 10, page no.d692-d697, October-2023, Available :http://www.ijnrd.org/papers/IJNRD2310393.pdf |
| Downloads: | 000118759 |
| ISSN: |
2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar| ESTD YEAR: 2016 An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.76 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator |
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Published Paper ID:IJNRD2310393 Registration ID: 207915 Published In: Volume 8 Issue 10, October-2023 DOI (Digital Object Identifier): Page No: d692-d697 Country: Chennai, Tamil Nadu, India Research Area: Science & Technology Publisher : IJ Publication Published Paper URL : https://www.ijnrd.org/viewpaperforall?paper=IJNRD2310393 Published Paper PDF: https://www.ijnrd.org/papers/IJNRD2310393 |
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ISSN: 2456-4184
Impact Factor: 8.76 and ISSN APPROVED
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