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| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11611389 | PMC |
| http://dx.doi.org/10.1080/24694452.2018.1535887 | DOI Listing |
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TCBGY net for enhanced wear particle detection in ferrography using self attention and multi scale fusion.
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Merchant Marine College, Shanghai Maritime University, Shanghai, 201306, China.
The intelligent identification of wear particles in ferrography is a critical bottleneck that hampers the development and widespread adoption of ferrography technology. To address challenges such as false detection, missed detection of small wear particles, difficulty in distinguishing overlapping and similar abrasions, and handling complex image backgrounds, this paper proposes an algorithm called TCBGY-Net for detecting wear particles in ferrography images. The proposed TCBGY-Net uses YOLOv5s as the backbone network, which is enhanced with several advanced modules to improve detection performance.
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Department of Chemistry, University of Washington, Box 351700, Seattle, Washington, 98195, USA.
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