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YOLO Detection.pdf

1506.02640.pdf
Preview of YOLO Detection
🔗 Source: arxiv.org
📊 Size: 5.05 MB
📄 Pages: 10 pages
⬇️ Downloads: 132

Summary

YOLO is a real-time object detection system that reframes detection as a regression problem, predicting bounding boxes and class probabilities directly from full images in one evaluation. It's extremely fast, processing images at 45 frames per second, and achieves more than twice the mean average precision of other real-time systems. YOLO reasons globally about the image, implicitly encoding contextual information, and learns generalizable representations of objects, outperforming other methods when generalizing to new domains. However, it still lags behind state-of-the-art detection systems in accuracy, struggling to precisely localize small objects.

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Description

YOLO is a real-time object detection system that reframes detection as a regression problem, predicting bounding boxes and class probabilities directly from...

Technical Information

  • File Format: PDF
  • File Size: 5.05 MB
  • Pages: 10
  • Language: EN
  • Total Downloads: 132
  • Last Updated: 2 hours ago

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This PDF document about YOLO Detection provides comprehensive information and guidance. Whether you're a beginner or advanced user, this resource offers valuable insights into YOLO Detection.

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