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Publication Date

2023-5

First Advisor

Nicholas Howe

Document Type

Honors Project

Degree Name

Bachelor of Arts

Department

Computer Science

Keywords

handwriting recognition, CRNN, CTC, Chu Nom manuscript handwriting recognition, RESNet, DenseNet

Abstract

Chu Nom is the ancient handwriting system of Vietnam from the 15th century till the 19th century. Due to various factors, we now have a large collection of digitized Nom manuscripts yet no way to properly and efficiently label and categorize them. In this thesis, we build multiple CRNN models for handwriting recognition for chu Nom. We utilized the dataset collected by the IHR-NomDB project, and perform experiments, evaluations and comparison of the models on this dataset. Our model achieved promising result on both the synthetic dataset and the actual handwriting dataset, which we hope will provide a basis for future research on the topic.

Rights

©2023 Phuong Phan. Access limited to the Smith College community and other researchers while on campus. Smith College community members also may access from off-campus using a Smith College log-in. Other off-campus researchers may request a copy through Interlibrary Loan for personal use.

Language

English

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