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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.<\/jats:p>","DOI":"10.3390\/computers14090396","type":"journal-article","created":{"date-parts":[[2025,9,18]],"date-time":"2025-09-18T12:24:25Z","timestamp":1758198265000},"page":"396","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["AI Test Modeling for Computer Vision System\u2014A Case Study"],"prefix":"10.3390","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-1051-5839","authenticated-orcid":false,"given":"Jerry","family":"Gao","sequence":"first","affiliation":[{"name":"Department of Computer Engineering, College of Engineering, San Jose State University, San Jose, CA 95192, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4601-2659","authenticated-orcid":false,"given":"Radhika","family":"Agarwal","sequence":"additional","affiliation":[{"name":"ALPSTouchStone, Inc., San Jose, CA 95192, USA"}]}],"member":"1968","published-online":{"date-parts":[[2025,9,18]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Gao, J., Agarwal, R., and Garsole, P. 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