AI Test Modeling for Computer Vision System—A Case Study

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Опубліковано в::	Computers vol. 14, no. 9 (2025), p. 396-418
Автор:	Gao, Jerry
Інші автори:	Agarwal Radhika
Опубліковано:	MDPI AG
Предмети:	Software Computer vision Artificial intelligence Automation Modelling Vision systems Autonomous vehicles
Онлайн доступ:	Citation/Abstract Full Text + Graphics Full Text - PDF
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Опис
Короткий огляд:	This paper presents an intelligent AI test modeling framework for computer vision systems, focused on image-based systems. A three-dimensional (3D) model using decision tables enables model-based function testing, automated test data generation, and comprehensive coverage analysis. A case study using the Seek by iNaturalist application demonstrates the framework’s applicability to real-world CV tasks. It effectively identifies species and non-species under varying image conditions such as distance, blur, brightness, and grayscale. This study contributes a structured methodology that advances our academic understanding of model-based CV testing while offering practical tools for improving the robustness and reliability of AI-driven vision applications.
ISSN:	2073-431X
DOI:	10.3390/computers14090396
Джерело:	Advanced Technologies & Aerospace Database