most citedPattern Generation Strategies for Improving Recognition of Handwritten Mathematical Expressions

5 citations · 16 across the 4 of their papers we have counts for

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cs.CV20203 cited

Automated Transcription for Pre-Modern Japanese Kuzushiji Documents by Random Lines Erasure and Curriculum Learning

Anh Duc Le

Recognizing the full-page of Japanese historical documents is a challenging problem due to the complex layout/background and difficulty of writing styles, such as cursive and conne…

cs.CV2019

Deep Learning Approach for Receipt Recognition

Anh Duc Le, Dung Van Pham, Tuan Anh Nguyen

Inspired by the recent successes of deep learning on Computer Vision and Natural Language Processing, we present a deep learning approach for recognizing scanned receipts. The reco…

cs.CV20194 cited

End to End Recognition System for Recognizing Offline Unconstrained Vietnamese Handwriting

Anh Duc Le, Hung Tuan Nguyen, Masaki Nakagawa

Inspired by recent successes in neural machine translation and image caption generation, we present an attention based encoder decoder model (AED) to recognize Vietnamese Handwritt…

cs.CV20194 cited

A human-inspired recognition system for premodern Japanese historical documents

Anh Duc Le, Tarin Clanuwat, Asanobu Kitamoto

Recognition of historical documents is a challenging problem due to the noised, damaged characters and background. However, in Japanese historical documents, not only contains the…

cs.CV20195 cited

Pattern Generation Strategies for Improving Recognition of Handwritten Mathematical Expressions

Anh Duc Le, Bipin Indurkhya, Masaki Nakagawa

Recognition of Handwritten Mathematical Expressions (HMEs) is a challenging problem because of the ambiguity and complexity of two-dimensional handwriting. Moreover, the lack of la…