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Detecting Concept Drift in Object Detection Models: A Collaborative AI-Human Approach for Defense Applications

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Published in:IEEE Access
Format: Online Article RSS Article
Published: 2026
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spellingShingle Detecting Concept Drift in Object Detection Models: A Collaborative AI-Human Approach for Defense Applications
Computer Science & Information Science
Computer Science & IT
Engineering & Technology
sub_discipline_display Computer Science & IT
sub_discipline_facet Computer Science & IT
subject_display Computer Science & Information Science
Computer Science & IT
Engineering & Technology
Computer Science & Information Science
Computer Science & IT
Engineering & Technology
subject_facet Computer Science & Information Science
Computer Science & IT
Engineering & Technology
title Detecting Concept Drift in Object Detection Models: A Collaborative AI-Human Approach for Defense Applications
title_auth Detecting Concept Drift in Object Detection Models: A Collaborative AI-Human Approach for Defense Applications
title_full Detecting Concept Drift in Object Detection Models: A Collaborative AI-Human Approach for Defense Applications
title_fullStr Detecting Concept Drift in Object Detection Models: A Collaborative AI-Human Approach for Defense Applications
title_full_unstemmed Detecting Concept Drift in Object Detection Models: A Collaborative AI-Human Approach for Defense Applications
title_short Detecting Concept Drift in Object Detection Models: A Collaborative AI-Human Approach for Defense Applications
title_sort detecting concept drift in object detection models: a collaborative ai-human approach for defense applications
topic Computer Science & Information Science
Computer Science & IT
Engineering & Technology
url http://ieeexplore.ieee.org/document/11340586