Young Researcher Paper Award 2023
🥇Winners

Notice of retraction
Vol. 34, No. 8(3), S&M3042

Notice of retraction
Vol. 32, No. 8(2), S&M2292

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.
Sensors and Materials
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 34, Number 5(1) (2022)
Copyright(C) MYU K.K.
pp. 1747-1756
S&M2925 Research Paper of Special Issue
https://doi.org/10.18494/SAM3822
Published: May 10, 2022

Misleading Video Detection Using Deep Image Retrieval and Dual-stage Confidence Filtering [PDF]

Yonghu Yang, Cheng-Fu Yang, and Chiang-Lung Lin

(Received December 30, 2021; Accepted March 31, 2022)

Keywords: misleading video detection, image retrieval, ensemble filtering, convolutional neural network

Computer vision technologies have recently been maliciously used to spread misleading information. Because of the low cost of video production, misleading videos have been used for attack ads, criminal fraud, and even political manipulation, which could undermine social progress. Hence, it is important to develop a system for detecting misleading videos that can help a fact-checking center detect misleading videos more efficiently. In this research, we propose a novel video retrieval system based on a deep convolutional neural network that extracts deep visual informatics to retrieve visually alike videos from annotated misleading videos. Moreover, we propose dual-stage confidence filtering that considers both video- and image-level retrieval. This is one of the latest studies on misleading video detection using video-level retrieval, and preliminary experiments demonstrate its superior retrieval performance, enabling it to be applied in real-world applications.

Corresponding author: Cheng-Fu Yang, Chiang-Lung Lin


Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.

Cite this article
Yonghu Yang, Cheng-Fu Yang, and Chiang-Lung Lin, Misleading Video Detection Using Deep Image Retrieval and Dual-stage Confidence Filtering, Sens. Mater., Vol. 34, No. 5, 2022, p. 1747-1756.



Forthcoming Regular Issues


Forthcoming Special Issues

Applications of Novel Sensors and Related Technologies for Internet of Things
Guest editor, Teen-Hang Meen (National Formosa University), Wenbing Zhao (Cleveland State University), and Cheng-Fu Yang (National University of Kaohsiung)
Call for paper


Special Issue on Advanced Data Sensing and Processing Technologies for Smart Community and Smart Life
Guest editor, Tatsuya Yamazaki (Niigata University)
Call for paper


Special Issue on Advanced Sensing Technologies and Their Applications in Human/Animal Activity Recognition and Behavior Understanding
Guest editor, Kaori Fujinami (Tokyo University of Agriculture and Technology)
Call for paper


Special Issue on International Conference on Biosensors, Bioelectronics, Biomedical Devices, BioMEMS/NEMS and Applications 2023 (Bio4Apps 2023)
Guest editor, Dzung Viet Dao (Griffith University) and Cong Thanh Nguyen (Griffith University)
Conference website
Call for paper


Special Issue on Piezoelectric Thin Films and Piezoelectric MEMS
Guest editor, Isaku Kanno (Kobe University)
Call for paper


Special Issue on Advanced Micro/Nanomaterials for Various Sensor Applications (Selected Papers from ICASI 2023)
Guest editor, Sheng-Joue Young (National United University)
Conference website
Call for paper


Copyright(C) MYU K.K. All Rights Reserved.