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.
导演吴炜伦接受采访时称，故事背景选择在2012年是因为那时那个行业还在运作，但已经开始有彷徨，“这种感觉同现在的香港有一点点相似。”，详情可参考服务器推荐
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Unlimited projects。关于这个话题，Line官方版本下载提供了深入分析
Universality is Key: