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Designing a Performance Certification Test for Automatic Detection Equipment based on Artificial Intelligence Technology

Ki-Yeon Kim, Jin-Hyeong Jung, Yeon Ah Yoon, Yong Soo Kim

2020Journal of Applied Reliability15 citationsDOI

Abstract

Purpose: This paper examined the design of a standard test method for certifying the performance of automatic detection equipment using artificial intelligence (AI).BRMethods: First, indicators for measuring the detection performance were determined and the terms were redefined. Then, the number of iterations required to give a criterion value at a given confidence level for data following the binomial distribution was calculated. As a case study, an aviation security x-ray scanner was tested.BRResults: If failures occur before the number of allowable times during the trial, the minimum probability of occurrence of true positive (TP) can be demonstrated. This means that F2-Score is satisfied, and the performance can be certified.BRConclusion: This method can be used in industries that operate automatic detectors based on AI technology. The method should contribute to the development of a national certification system and improve product quality control.

Topics & Concepts

CertificationReliability engineeringComputer scienceAviationQuality (philosophy)Binomial distributionArtificial intelligenceStatisticsData miningEngineeringMathematicsPhilosophyPolitical scienceLawAerospace engineeringEpistemologyTechnology and Data Analysis
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