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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: | Incremental Learning for Efficient Object Detection in Autonomous Vehicles |
| Authors Name: | Navjot Singh , Vivek Kumar |
| Download E-Certificate: | Download |
| Author Reg. ID: |
IJNRD_217404
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| Published Paper Id: | IJNRD2404113 |
| Published In: | Volume 9 Issue 4, April-2024 |
| DOI: | |
| Abstract: | Object detection is a critical task for autonomous vehicles, enabling them to perceive and understand their surroundings accurately and in real-time. However, traditional object detection methods often struggle to adapt to the dynamic nature of real-world environments, leading to performance degradation and potential safety risks. This research proposes an incremental learning framework for efficient object detection in autonomous vehicles, addressing the challenges of continuous learning and adaptation. By leveraging techniques such as knowledge distillation, data augmentation, and regularization, the proposed approach allows the object detection model to incrementally learn from new data while retaining previously acquired knowledge. The framework is designed to strike a balance between accuracy and computational efficiency, enabling real-time performance on embedded systems. Extensive experiments on public datasets demonstrate the effectiveness of the proposed method, outperforming existing approaches in terms of detection accuracy and computational efficiency. The research also explores practical considerations for deployment, safety, and robustness, paving the way for reliable and adaptable object detection in autonomous driving scenarios. |
| Keywords: | Object Detection, Autonomous Vehicles, Incremental Learning, Deep Learning, Knowledge Distillation, Data Augmentation, Computational Efficiency, Real-time Systems. |
| Cite Article: | "Incremental Learning for Efficient Object Detection in Autonomous Vehicles", International Journal of Novel Research and Development (www.ijnrd.org), ISSN:2456-4184, Vol.9, Issue 4, page no.b91-b96, April-2024, Available :http://www.ijnrd.org/papers/IJNRD2404113.pdf |
| Downloads: | 00065 |
| 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:IJNRD2404113 Registration ID: 217404 Published In: Volume 9 Issue 4, April-2024 DOI (Digital Object Identifier): Page No: b91-b96 Country: LUDHIANA, Punjab, India Research Area: Engineering Publisher : IJ Publication Published Paper URL : https://www.ijnrd.org/viewpaperforall?paper=IJNRD2404113 Published Paper PDF: https://www.ijnrd.org/papers/IJNRD2404113 |
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ISSN: 2456-4184
Impact Factor: 8.76 and ISSN APPROVED
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