Fully Convolutional Networks for Handwriting Recognition

Such, Felipe Petroski; Peri, Dheeraj; Brockler, Frank; Hutkowski, Paul; Ptucha, Raymond

doi:10.48550/arxiv.1907.04888

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2021

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“…Handwriting recognition with vision-based approaches like Optical Character Recognition (OCR) [1] and on-screen stroke-detection has been successful in many applications [2,3,4,5]. However, such applications or device often require touch screens or digitizers, which are often expensive and pose an unnecessary restriction to users.…”

Section: Introductionmentioning

confidence: 99%

Motion-Based Handwriting Recognition and Word Reconstruction

Chen¹,

Xie²,

He³

2021

Preprint

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In this project, we leverage a trained single-letter classifier to predict the written word from a continuously written word sequence, by designing a word reconstruction pipeline consisting of a dynamicprogramming algorithm and an auto-correction model. We conduct experiments to optimize models in this pipeline, then employ domain adaptation to explore using this pipeline on unseen data distributions.

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Section: Introductionmentioning

confidence: 99%