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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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丹期也表示，他很清楚中期選舉的影響，也警惕剩下三年多任期時間有限：「沙漏正慢慢流逝，時間正在被浪費。」。爱思助手下载最新版本对此有专业解读