Diqun Yan on Muck Rack

Diqun Yan

As seen in: Taylor & Francis Online
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Articles

Vehicle re-identification based on suppressing contaminated features

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By Xuan Ning, Jiangbo Qian, Li Dong, Diqun Yan
| Taylor & Francis Online
Abstract With the dramatic increase in the number of vehicles, the task of vehicle re-identification has attracted widespread attention, especially in the fields of traffic supervision and criminal investigation. Although good methods have been proposed, key problems remain: (1) Models are susceptible to noise interference.
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Evil Operation: Breaking Speaker Recognition with PaddingBack

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By Diqun Yan, Li Dong, Kailai Shen
| arxiv.org
arXiv:2308.04179 (cs) Download a PDF of the paper titled Evil Operation: Breaking Speaker Recognition with PaddingBack, by Zhe Ye and 3 other authors Download PDF Submission history From: Diqun Yan [ view email] [v1] Tue, 8 Aug 2023 10:36:44 UTC (2,836 KB) Bibliographic Tools Bibliographic Explorer Toggle Bibliographic Explorer () Litmaps Toggle Litmaps (What is Litmaps?) scite.ai Toggle scite Smart Citations (What are Smart Citations?) Code, Data, Media Links to Code Toggle CatalyzeX Code...
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Universal Defensive Underpainting Patch: Making Your Text Invisible to Optical Character Recognition

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By Li Dong, Jiahao Chen, Diqun Yan, Rangding Wang
| arxiv.org
Optical Character Recognition (OCR) enables automatic text extraction from scanned or digitized text images, but it also makes it easy to pirate valuable or sensitive text from these images. Previous methods to prevent OCR piracy by distorting characters in text images are impractical in real-world scenarios, as pirates can capture arbitrary portions of the text images, rendering the defenses ineffective.
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