GlyphNet’s own results support this: their best CNN (VGG16 fine-tuned on rendered glyphs) achieved 63-67% accuracy on domain-level binary classification. Learned features do not dramatically outperform structural similarity for glyph comparison, and they introduce model versioning concerns and training corpus dependencies. For a dataset intended to feed into security policy, determinism and auditability matter more than marginal accuracy gains.
2026-02-28 00:00:00:03014270810http://paper.people.com.cn/rmrb/pc/content/202602/28/content_30142708.htmlhttp://paper.people.com.cn/rmrb/pad/content/202602/28/content_30142708.html11921 2026年全国两会新闻中心启用
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