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.
2021—2025 年度，无论披露研发投入的企业数量/占比，还是研发投入总额/平均值，都呈整体上升趋势。
。快连下载安装是该领域的重要参考
Online Safety Bill
type=image — push to a registry (the default for docker build)