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Counting With Regression Forest.pdf

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Preview of Counting with Regression Forest
🔗 Source: hci.iwr.uni-heidelberg.de
📊 Size: 3.66 MB
📄 Pages: 4 pages
⬇️ Downloads: 415

Summary

The authors propose a method for object counting in images by integrating over an object density map predicted from an input image. They use a regression forest to estimate the object density map by averaging over structured, patch-wise predictions. The method achieves similar quality results to existing approaches but with reduced training time and implementation effort. The authors also introduce an uncertainty measure for the predicted object density using the random forest out-of-bag samples. Experiments demonstrate favorable results compared to state-of-the-art methods.

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Description

The authors propose a method for object counting in images by integrating over an object density map predicted from an input image.

Technical Information

  • File Format: PDF
  • File Size: 3.66 MB
  • Pages: 4
  • Language: EN
  • Total Downloads: 415
  • Last Updated: 3 hours ago

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

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