
Huanhuan Zhang
Articles
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3 weeks ago |
mdpi.com | Jing Yuan |Pei Li |Huanhuan Zhang |Shubiao Yin
1. IntroductionSteel reinforcement corrosion is a global issue affecting construction engineering, with chloride-induced corrosion being a leading cause of premature structural failure in coastal countries such as those in Europe, the US, Japan, South Korea, and Australia [1,2,3]. Chloride ions penetrate concrete and reach the steel surface, where they crystallize and cause localized corrosion, which can transition to uniform corrosion, impacting the service life of concrete structures.
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Jan 10, 2025 |
onlinelibrary.wiley.com | Wenwen Fang |Hojjat Asadollahpour Nanaei |Yu Chi Liu |Huanhuan Zhang
CONFLICT OF INTEREST STATEMENT The authors declare that they have no competing interests. Supporting Information Filename Description age13500-sup-0001-AppendixS1.pdfPDF document, 1.6 MB Appendix S1. age13500-sup-0002-AppendixS2.xlsxExcel 2007 spreadsheet , 48.6 KB Appendix S2. REFERENCES & (2011) Enhancements to the ADMIXTURE algorithm for individual ancestry estimation. BMC Bioinformatics, 12, 246. , , , , , et al.
RAAFNet: Reverse Attention Adaptive Fusion Network for Large-Scale Point Cloud Semantic Segmentation
Aug 12, 2024 |
mdpi.com | Kai Wang |Huanhuan Zhang
All articles published by MDPI are made immediately available worldwide under an open access license. No special permission is required to reuse all or part of the article published by MDPI, including figures and tables. For articles published under an open access Creative Common CC BY license, any part of the article may be reused without permission provided that the original article is clearly cited. For more information, please refer to https://www.mdpi.com/openaccess.
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Apr 8, 2024 |
nature.com | Huanhuan Zhang
AbstractThe current state-of-the-art anomaly detection methods based on knowledge distillation (KD) typically depend on smaller student networks or reverse distillation to address vanishing representations discrepancy on anomalies. These methods often struggle to achieve precise detection when dealing with complex texture backgrounds containing anomalies due to the similarity between anomalous and non-anomalous regions.
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