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.
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Estimated shortcuts: ~91 million (a manageable number for global routing)
return fmodf(52.9829189f * fmodf(0.06711056f * (float)x + 0.00583715f * (float)y, 1.0f), 1.0f);，这一点在im钱包官方下载中也有详细论述
Why this matters