AI Test Modeling for Computer Vision System—A Case Study
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| Publicado en: | Computers vol. 14, no. 9 (2025), p. 396-418 |
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| Autor principal: | |
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| Publicado: |
MDPI AG
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| Materias: | |
| Acceso en línea: | Citation/Abstract Full Text + Graphics Full Text - PDF |
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| 022 | |a 2073-431X | ||
| 024 | 7 | |a 10.3390/computers14090396 |2 doi | |
| 035 | |a 3254482230 | ||
| 045 | 2 | |b d20250101 |b d20251231 | |
| 084 | |a 231447 |2 nlm | ||
| 100 | 1 | |a Gao, Jerry |u Department of Computer Engineering, College of Engineering, San Jose State University, San Jose, CA 95192, USA; jerry.gao@sjsu.edu | |
| 245 | 1 | |a AI Test Modeling for Computer Vision System—A Case Study | |
| 260 | |b MDPI AG |c 2025 | ||
| 513 | |a Journal Article | ||
| 520 | 3 | |a 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. | |
| 653 | |a Software | ||
| 653 | |a Computer vision | ||
| 653 | |a Artificial intelligence | ||
| 653 | |a Automation | ||
| 653 | |a Modelling | ||
| 653 | |a Vision systems | ||
| 653 | |a Autonomous vehicles | ||
| 700 | 1 | |a Agarwal Radhika |u ALPSTouchStone, Inc., San Jose, CA 95192, USA | |
| 773 | 0 | |t Computers |g vol. 14, no. 9 (2025), p. 396-418 | |
| 786 | 0 | |d ProQuest |t Advanced Technologies & Aerospace Database | |
| 856 | 4 | 1 | |3 Citation/Abstract |u https://www.proquest.com/docview/3254482230/abstract/embedded/L8HZQI7Z43R0LA5T?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text + Graphics |u https://www.proquest.com/docview/3254482230/fulltextwithgraphics/embedded/L8HZQI7Z43R0LA5T?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text - PDF |u https://www.proquest.com/docview/3254482230/fulltextPDF/embedded/L8HZQI7Z43R0LA5T?source=fedsrch |