English(EN) YOLOv8 to YOLO11: A Comprehensive Architecture In-depth Comparative Review

YOLOv8 到 YOLO11：评测详述架构演进与挑战

作者 PulseAugur 编辑部 · [1 个来源] · 2026-04-28 04:00

本文对 YOLOv8 至 YOLO11 的计算机视觉模型进行了详细的比较评测。旨在阐明这些快速发展的目标检测系统的架构和区别，其中许多系统缺乏官方文档或学术出版物。该分析基于学术论文、文档和源代码审查，强调了各版本之间一致的架构模块，并指出了特征提取方面的改进。 AI

影响为流行的目标检测模型的架构演进提供了清晰的认识，帮助开发人员理解和使用它们。

排序理由这是一篇分析现有模型的学术论文，而非新模型的发布或重大的行业事件。

AI 生成摘要 · Google Gemini · 来自 1 个来源。我们如何撰写摘要 →

本文如何被排名

Signal score: 0 / 100; Composite score across the factors below. Higher = stronger signal that this story matters right now.
Newsworthiness bucket: Research; 这是一篇分析现有模型的学术论文，而非新模型的发布或重大的行业事件。
Source corroboration: Single-source cluster; Only one publisher covered this so far. Single-source stories can still rank when the publisher is high-authority, but they lack cross-source corroboration.
Topics: paper, other; Editorial topic classification. Feeds into how the story surfaces on /topic/<slug> hub pages and into the per-entity coverage mix.
AI-industry relevance: High; Clearly on-topic for AI-industry coverage.
Story freshness: 165 days old; Aged out of breaking-news scoring windows; ranking reflects the durable signal from the full source set.

完整方法见我们的编辑标准。

arXiv cs.CV TIER_1 English(EN) · Priyanto Hidayatullah, Nurjannah Syakrani, Muhammad Rizqi Sholahuddin, Trisna Gelar, Refdinal Tubagus · 2026-04-28 04:00

YOLOv8 到 YOLO11：全面的架构深度比较评测

arXiv:2501.13400v3 Announce Type: replace Abstract: In the field of deep learning-based computer vision, YOLO is revolutionary. With respect to deep learning models, YOLO is also the one that is evolving the most rapidly. Unfortunately, not every YOLO model possesses scholarly pu…