| Autor: |
Yiming Li, Lixin He, Min Zhang, Zhi Cheng, Wangwei Liu, Zijun Wu |
| Jazyk: |
angličtina |
| Rok vydání: |
2023 |
| Předmět: |
|
| Zdroj: |
Electronics; Volume 12; Issue 11; Pages: 2440 |
| ISSN: |
2079-9292 |
| DOI: |
10.3390/electronics12112440 |
| Popis: |
Strip surface defects have large intraclass and small interclass differences, resulting in the available detection techniques having either a low accuracy or very poor real-time performance. In order to improve the ability for capturing steel surface defects, the context fusion structure introduces the local information of the shallow layer and the semantic information of the deep layer into multiscale feature maps. In addition, for filtering the semantic conflicts and redundancies arising from context fusion, a feature refinement module is introduced in our method, which further improves the detection accuracy. Our experimental results show that this significantly improved the performance. In particular, our method achieved 79.5% mAP and 71 FPS on the public NEU-DET dataset. This means that our method had a higher detection accuracy compared to other techniques. |
| Databáze: |
OpenAIRE |
| Externí odkaz: |
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