SOURCE-LINKED INTELLIGENCE

Rethinking Handwritten Character Recognition

arXiv · AI, language, vision and robotics · article · Sep 2, 2026 · UTC

Non-Latin handwritten character recognition (HCR) remains understudied. Dominant methods consider it as generic image classification, which uses model scale to implicitly learn stroke structure. Structural-prior efficiency---the principle that explicitly encoding script-geometric regularities as architectural inductive biases can be both more accurate and require fewer parameters. We introduce GraphemeNet, a unified multi-script architecture, governed by two orthogonal binary axes. Axis 1 operationalises stroke-level geometric regularity via Persistent Scaffold Injection (PSI): a script-specif

Read original source ↗ Open in workspace

recordType

paper

region

Global