This paper provides a detailed comparative review of the YOLOv8 through YOLO11 computer vision models. It aims to clarify the architectures and distinctions between these rapidly evolving object detection systems, many of which lack official documentation or scholarly publications. The analysis, based on academic papers, documentation, and source code scrutiny, highlights consistent architectural blocks across versions while noting improvements in feature extraction. AI
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IMPACT Provides clarity on the architectural evolution of popular object detection models, aiding developers in understanding and utilizing them.
RANK_REASON This is a research paper analyzing existing models, not a release of a new model or a significant industry event.