CNN-Based Page Segmentation and Object Classification for Counting Population in Ottoman Archival Documentation
Historical document analysis systems gain importance with the increasing efforts in the digitalization of archives. Page segmentation and layout analysis are crucial steps for such systems. Errors in these steps will affect the outcome of handwritten text recognition and Optical Character Recognitio...
Main Authors: | Yekta Said Can, M. Erdem Kabadayı |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2020-05-01
|
Series: | Journal of Imaging |
Subjects: | |
Online Access: | https://www.mdpi.com/2313-433X/6/5/32 |
Similar Items
-
Automatic Estimation of Age Distributions from the First Ottoman Empire Population Register Series by Using Deep Learning
by: Yekta Said Can, et al.
Published: (2021-09-01) -
Automatic CNN-Based Arabic Numeral Spotting and Handwritten Digit Recognition by Using Deep Transfer Learning in Ottoman Population Registers
by: Yekta Said Can, et al.
Published: (2020-08-01) -
Benkő, Elek, Sándor, Klára, Vásáry, István: A székely írás emlékei. Corpus Monumentorum Alphabeto Siculico Exaratorum (CMASE)
by: László Károly
Published: (2023-04-01) -
Investigating Attention Mechanism for Page Object Detection in Document Images
by: Shivam Naik, et al.
Published: (2022-07-01) -
Exploring page layout principles in Iranian manuscripts: A comprehensive review from Seljuk to Safavid Era
by: Haniyeh Safari, et al.
Published: (2023-11-01)