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The Science of Catching Hidden Scope: Small Object Detection.

Discover how advanced Computer Vision models identify the buried callouts, symbols, and keynotes that human reviewers miss.

Construction drawings are visually chaotic. Finding a single mismatched door tag or a broken callout reference on a dense, 500-page PDF is like finding a needle in a haystack, yet missing it can cost tens of thousands of dollars in rework.


Standard text-based search tools fail because drawing symbols are graphical, not structural. To achieve true automated QA/QC, software must literally "see" the drawings.

Inside this technical white paper, you will learn:

  • The Core Challenge: Why traditional OCR (Optical Character Recognition) fails on complex architectural plans.
  • CNNs vs. VLMs: A technical comparison of Convolutional Neural Networks versus Vision-Language Models in detecting tiny graphical symbols.
  • Detection at Scale: How MarkedUp's proprietary models find buried callouts across large, dense drawing sets.

Enter your details to access the research.