A Transformer Architecture for Online Gesture Recognition of Mathematical Expressions

The Transformer architecture is shown to provide a powerful framework as an end-to-end model for building expression trees from online handwritten gestures corresponding to glyph strokes. In particular, the attention mechanism was successfully used to encode, learn and enforce the underlying syntax...

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Veröffentlicht in:	arXiv.org 2022-11
Hauptverfasser:	Ramo, Mirco, Silvestre, Guénolé C M
Format:	Artikel
Sprache:	eng
Schlagworte:	Ablation Coders Gesture recognition Handwriting Handwriting recognition Mathematical analysis Representations Robustness (mathematics)
Online-Zugang:	Volltext
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