Methods › Computer Vision › Convolutional Neural Networks › Fast-YOLOv2
Fast-YOLOv2
Introduced by Joseph Redmon et al. in YOLO9000: Better, Faster, Stronger
archive 2025-07-28 Description, source and code snippet are the archive's method entry.
The archive carries no description for this method.
Papers archive 2025-07-28
5 shown of 5, newest first. Repository counts are the archive's code-links table. A Syntology line states what Syntology ran from that paper's harvested code; it is per sample and not a correctness claim.
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Deep Learning for Image-based Automatic Dial Meter Reading: Dataset and Baselines 6 May 2020 · 0 repositories · arXiv:2005.03106
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An Efficient and Layout-Independent Automatic License Plate Recognition System Based on the YOLO detector 4 Sep 2019 · 1 repository · arXiv:1909.01754
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Convolutional Neural Networks for Automatic Meter Reading 25 Feb 2019 · 0 repositories · arXiv:1902.09600
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A Robust Real-Time Automatic License Plate Recognition Based on the YOLO Detector 26 Feb 2018 · 2 repositories · arXiv:1802.09567
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YOLO9000: Better, Faster, Stronger 25 Dec 2016 · 231 repositories · arXiv:1612.08242Syntology ran 16 of 60 samples · 44 unverified · 22 pointer-only (licence)
Tasks archive 2025-07-28
15 tasks the archive attaches to papers tagged with this method, by distinct papers. A task without a page in the catalog is plain text.
Usage over time archive 2025-07-28
Components: the archive holds no method-to-method composition, so PwC's Components table cannot be rebuilt; the Papers list carries no Results column for the same reason (the archive does not join its leaderboard rows to method tags).
Categories archive 2025-07-28
Report a problem or propose a change · a person checks every report against the paper or source before anything changes; decisions are listed on /corrections