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Moving Vehicle Tracking And Scene Understanding: A Hybrid Approach..pdf

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Preview of Moving vehicle tracking and scene understanding: A hybrid approach.
🔗 Source: cerv.aut.ac.nz
📊 Size: 1.31 MB
📄 Pages: 22 pages
⬇️ Downloads: 90

Summary

A novel deep learning method for detecting and tracking vehicles in autonomous driving scenarios is presented, focusing on vehicle failures. A hybrid Siamese network combining YOLO models with Transformers is introduced to address CNN limitations in grasping high-level semantic nuances, facilitating accurate detection and tracking of multiple vehicles. A traffic scene dataset is also curated for training a multi-vehicle tracking model. The method integrates visual features from YOLO and Siamese networks with Transformer and attention modules to understand high-level scene semantics, improving local and global feature extraction abilities.

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Description

A novel deep learning method for detecting and tracking vehicles in autonomous driving scenarios is presented, focusing on vehicle failures.

Technical Information

  • File Format: PDF
  • File Size: 1.31 MB
  • Pages: 22
  • Language: EN
  • Total Downloads: 90
  • Last Updated: 5 days ago

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