Young Researcher Paper Award 2025
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Print: ISSN 0914-4935
Online: ISSN 2435-0869
Sensors and Materials
is an international peer-reviewed open access journal to provide a forum for researchers working in multidisciplinary fields of sensing technology.
Online: ISSN 2435-0869
Sensors and Materials
is an international peer-reviewed open access journal to provide a forum for researchers working in multidisciplinary fields of sensing technology.
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Sensors and Materials
is covered by Science Citation Index Expanded (Clarivate Analytics), Scopus (Elsevier), and other databases.
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Sensors and Materials
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is covered by Science Citation Index Expanded (Clarivate Analytics), Scopus (Elsevier), and other databases.
Instructions to authors
English 日本語
Instructions for manuscript preparation
English 日本語
Template
English
Publisher
MYU K.K.
Sensors and Materials
1-23-3-303 Sendagi,
Bunkyo-ku, Tokyo 113-0022, Japan
Tel: 81-3-3827-8549
Fax: 81-3-3827-8547
MYU Research, a scientific publisher, seeks a native English-speaking proofreader with a scientific background. B.Sc. or higher degree is desirable. In-office position; work hours negotiable. Call 03-3827-8549 for further information.
MYU Research
(proofreading and recording)
MYU K.K.
(translation service)
The Art of Writing Scientific Papers
(How to write scientific papers)
(Japanese Only)
Sensors and Materials, Volume 37, Number 2(3) (2025)
Copyright(C) MYU K.K.
Copyright(C) MYU K.K.
|
pp. 783-794
S&M3956 Research Paper of Special Issue https://doi.org/10.18494/SAM5509 Published: February 28, 2025 Change Detection of Historical Villages in the Korean Demilitarized Zone Using a CNN Model: Focusing on Villages within the Korean Demilitarized Zone during the 1910s and 1950s [PDF] Haeyong Jeong (Received December 19, 2024; Accepted February 21, 2025) Keywords: demilitarized zone, deep learning, convolutional neural network, temporal-spatial analysis, historical topographic maps
In this study, we investigated the spatial and temporal changes in village distributions within the Korean Peninsula’s Demilitarized Zone (DMZ) using deep learning methods. Historical maps from the 1910s and 1950s were analyzed to analyze house distributions and identify changes caused by historical events. A custom convolutional neural network model was developed for automated feature extraction, achieving high accuracy compared with traditional methods. The findings provide foundational data for understanding the historical continuity of settlements within the DMZ and aim to support future research on its restoration and development.
Corresponding author: Haeyong Jeong  This work is licensed under a Creative Commons Attribution 4.0 International License. Cite this article Haeyong Jeong, Change Detection of Historical Villages in the Korean Demilitarized Zone Using a CNN Model: Focusing on Villages within the Korean Demilitarized Zone during the 1910s and 1950s, Sens. Mater., Vol. 37, No. 2, 2025, p. 783-794. |
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