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| Main Authors: | , , , , |
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| Format: | Recurso digital |
| Language: | English |
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Zenodo
2026
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| Online Access: | https://doi.org/10.5281/zenodo.19603081 |
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| _version_ | 1866901504633339904 |
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| author | Atchaya K Madhumitha T Pasumarthini R Siva Sandhiya M Susmitha S |
| author_facet | Atchaya K Madhumitha T Pasumarthini R Siva Sandhiya M Susmitha S |
| contents | The rapid growth of urbanization has resulted in increased vehicle density on roads, raising the demand for efficient and intelligent traffic monitoring systems. This paper presents a real-time vehicle detection, tracking, and recognition system using YOLOv26(ultralytics), the latest advancement in the You Only Look Once (YOLO) architecture. The proposed system leverages deep learning-based object detection to detect and classify vehicles from video streams captured by surveillance cameras. YOLOv26(ultralytics) offers improved accuracy and speed over its predecessors, making it highly suitable for real-time Intelligent Transportation System (ITS) applications. The system incorporates Deep SORT for robust multi-object tracking and supports recognition based on vehicle attributes including color, type, and license plate. |
| format | Recurso digital |
| id | zenodo_https___doi_org_10_5281_zenodo_19603081 |
| institution | Zenodo |
| language | eng |
| publishDate | 2026 |
| publisher | Zenodo |
| record_format | zenodo |
| spellingShingle | Real-Time Vehicle Detection, Tracking And Recognition Using YOLOv26 (Ultralytics) Atchaya K Madhumitha T Pasumarthini R Siva Sandhiya M Susmitha S The rapid growth of urbanization has resulted in increased vehicle density on roads, raising the demand for efficient and intelligent traffic monitoring systems. This paper presents a real-time vehicle detection, tracking, and recognition system using YOLOv26(ultralytics), the latest advancement in the You Only Look Once (YOLO) architecture. The proposed system leverages deep learning-based object detection to detect and classify vehicles from video streams captured by surveillance cameras. YOLOv26(ultralytics) offers improved accuracy and speed over its predecessors, making it highly suitable for real-time Intelligent Transportation System (ITS) applications. The system incorporates Deep SORT for robust multi-object tracking and supports recognition based on vehicle attributes including color, type, and license plate. |
| title | Real-Time Vehicle Detection, Tracking And Recognition Using YOLOv26 (Ultralytics) |
| url | https://doi.org/10.5281/zenodo.19603081 |