Maritime Small Target Image Detection Algorithm Based on Improved YOLOv11n
Zhaohua Liu, Yanli Sun, Pengfei He, Ningbo Liu, Zhongxun Wang · 2025
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Description
Zhaohua Liu and four co-authors improve a fast object-spotting model so it can find small ships at sea. Their 2025 paper starts from YOLOv11n, a light model that often misses tiny boats against cluttered waves. Small patrol boats carry few visual cues. That raises the miss rate.
The team adds three parts to the model. One blends infrared and visible-light views. A backbone block picks up fine local detail. A closing block traces small outlines with shifting filters. On two ship image sets the tuned model raised detection scores by about two points while adding few parameters. The authors say the gains matter for sea patrol and safety watch tasks.
Catalog record
| CREATOR | Zhaohua Liu, Yanli Sun, Pengfei He, Ningbo Liu, Zhongxun Wang |
|---|---|
| YEAR | 2025 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 34 KB |
| VERSION | 1.0 |
| LICENSE | CC BY 4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |