Machine Vision & Industrial Inspection AI calculator

AI Inspection Precision and Recall Calculator

Recall (also called sensitivity or detection rate) measures the percentage of actual defects that the AI inspection model correctly detects. A model with 98 percent recall misses 2 percent of defective parts. Enter the number of true positives (defects correctly detected by the model) and the total number of actual defects in the validation sample (true positives plus false negatives). The calculator returns recall and the gap to your required specification. Use this alongside precision (which measures false reject rate) to fully characterize AI model performance before production release.

What this calculator does

  • Calculate the recall (sensitivity) of an AI inspection model from a validation sample by dividing true positives by the total number of actual defects, and see how far the result is from your required detection specification.
  • Use it when validating an AI inspection model against a known-defect sample set and you need to calculate and document detection recall before releasing the model to production.
  • Turns true positives (defects correctly detected), total actual defects in validation sample, required detection recall specification into a rate for ai inspection precision recall in machine vision and industrial inspection ai.

Formula used

  • Recall = true positives / total actual defects x 100
  • Gap to specification = required recall - current recall

Inputs explained

  • True positives (defects correctly detected): Enter the number of actual defective parts that the AI model correctly flagged as defective in the validation run.
  • Total actual defects in validation sample: Enter the total confirmed defect count from the labeled validation dataset. This is true positives plus false negatives (defects the model missed).
  • Required detection recall specification: Enter the minimum recall required by your quality standard, customer specification, or AI system validation plan. Many safety and food applications require 98 to 99.9 percent.

How to use the result

  • Use it when ai inspection precision recall in machine vision and industrial inspection ai is being reviewed against a KPI.
  • Trend matters more than a single snapshot; pull the result for the last several periods before you act.

Common questions

  • What does the ai inspection precision recall calculator give me? Calculate the recall (sensitivity) of an AI inspection model from a validation sample by dividing true positives by the total number of actual defects, and see how far the result is from your required detection specification. You get a rate you can defend before quoting, scheduling, or sign-off.
  • What numbers should I focus on first? true positives (defects correctly detected), total actual defects in validation sample, required detection recall specification usually move the rate most. Pull from measured machine vision and industrial inspection ai runs, supplier data, and recent quotes rather than memory.
  • How should I use the result? Use the gap to target to prioritize the next machine vision and industrial inspection ai kaizen or corrective action.
  • What can throw the result off? Confirm the counts came from the same time window and the same scope; mismatched scope is the most common error.

Last reviewed 2026-05-12.