AI Test Modeling for Computer Vision System—A Case Study
محفوظ في:
| الحاوية / القاعدة: | Computers vol. 14, no. 9 (2025), p. 396-418 |
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| المؤلف الرئيسي: | |
| مؤلفون آخرون: | |
| منشور في: |
MDPI AG
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| الموضوعات: | |
| الوصول للمادة أونلاين: | Citation/Abstract Full Text + Graphics Full Text - PDF |
| الوسوم: |
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| مستخلص: | 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. |
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| تدمد: | 2073-431X |
| DOI: | 10.3390/computers14090396 |
| المصدر: | Advanced Technologies & Aerospace Database |