Methods › Computer Vision › Convolutional Neural Networks › Fast-YOLOv4-SmallObj
Fast-YOLOv4-SmallObj
Introduced by Rayson Laroca et al. in Towards Image-based Automatic Meter Reading in Unconstrained Scenarios: A Robust and Efficient Approach
archive 2025-07-28 Description, source and code snippet are the archive's method entry.
The Fast-YOLOv4-SmallObj model is a modified version of Fast-YOLOv4 to improve the detection of small objects. Seven layers were added so that it predicts bounding boxes at 3 different scales instead of 2.
Papers archive 2025-07-28
2 shown of 2, 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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Fire Detection From Image and Video Using YOLOv5 10 Oct 2023 · 0 repositories · arXiv:2310.06351
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Towards Image-based Automatic Meter Reading in Unconstrained Scenarios: A Robust and Efficient Approach 21 Sep 2020 · 0 repositories · arXiv:2009.10181
Tasks archive 2025-07-28
6 tasks the archive attaches to papers tagged with this method, by distinct papers. A task without a page in the catalog is plain text.
| Task | Papers |
|---|---|
| Fire Detection | 1 |
| Image-based Automatic Meter Reading | 1 |
| Meter Reading | 1 |
| Object Detection | 1 |
| Optical Character Recognition (OCR) | 1 |
| object-detection | 1 |
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