A Methodological Study of Document Layout Analysis-Reference-Cited by-同舟云学术

A Methodological Study of Document Layout Analysis

Published:2022-10 Issue: Volume: Page:
ISSN:
Container-title:2022 International Conference on Virtual Reality, Human-Computer Interaction and Artificial Intelligence (VRHCIAI)
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Author:

Zhang Chunhu¹,Ibrayim Mayire¹,Hamdulla Askar¹

Affiliation:

1. Xinjiang Key Laboratory of Signal Detection and Processing,Urumqi,China,830017

Funder

National Natural Science Foundation of China

Natural Science Foundation of Xinjiang

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10062102/10062866/10062927.pdf?arnumber=10062927

Reference37 articles.

1. PubLayNet: Largest Dataset Ever for Document Layout Analysis

2. Layout Analysis for Arabic Historical Document Images Using Machine Learning

3. ICDAR 2019 Competition on Recognition of Documents with Complex Layouts-RDCL2019;clausner;2019 International Conference on Document Analysis and Recognition (ICDAR),0

4. An adaptive over-split and merge algorithm for page segmentation

5. Vision-Based Layout Detection from Scientific Literature using Recurrent Convolutional Neural Networks

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