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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。搜狗输入法2026是该领域的重要参考
物理世界的重建，才刚刚开始。而与此同时，在离普通人最近的消费端，一场新的入口争夺战也正在悄悄打响。
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Source: Computational Materials Science, Volume 267。旺商聊官方下载对此有专业解读