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.
Последние новости
新时代以来，幼有所育、学有所教、劳有所得、病有所医、老有所养、住有所居、弱有所扶……在以习近平同志为核心的党中央坚强领导下，我们一件接着一件办，一年接着一年干。我们取得的一切原创性思想、变革性实践、突破性进展、标志性成果，无不闪耀着一个光辉的起点——为了人民。
第五十七条 国家建立核损害赔偿责任制度，按照法律和国家有关规定处理核事故造成的损害。