For more from Mashable's interview with Matthew Lillard, including his thoughts on Thirteen Ghosts, his advice to young actors, what he learned from the Quentin Tarantino incident, and his love of Dungeons and Dragons, check out the full interview on our YouTube channel.
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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.