Ok_Regular_8225
[qjoly@fedora]~% rpm-ostree status
，这一点在safew官方下载中也有详细论述
Фото: Kevin Coombs / Reuters
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.