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.
한동훈 “백의종군 하라? 그분들, 尹이 보수 망칠때 뭐했나”
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'A dangerous precedent'
Estonian PM: If Putin stops Russia's war in Ukraine, he falls