发布求助
文献互助 智能选刊 最新文献

2020 International Conference on Information and Communication Technology Convergence (ICTC)最新文献

筛选
英文 中文
Feature Extraction Model Based on Inception V3 to Distinguish Normal Heart Sound from Systolic Murmur 基于Inception V3的正常心音与收缩期杂音的特征提取模型
2020 International Conference on Information and Communication Technology Convergence (ICTC) Pub Date : 2020-10-21 DOI: 10.1109/ICTC49870.2020.9289317
Jinhee Bae, Minwoo Kim, J. Lim
{"title":"Feature Extraction Model Based on Inception V3 to Distinguish Normal Heart Sound from Systolic Murmur","authors":"Jinhee Bae, Minwoo Kim, J. Lim","doi":"10.1109/ICTC49870.2020.9289317","DOIUrl":"https://doi.org/10.1109/ICTC49870.2020.9289317","url":null,"abstract":"In this study, we propose a model for classifying normal and abnormal sounds by extracting characteristics from abnormal heart sounds in which normal and symbolic murmurs appear. Heart sound data obtained through an electronic stethoscope are converted into mel-spectrogram images. The pre-trained Inception V3 model that carries out fine-tuning uses the mel-spectrogram image as input. Convolutional layers of fine-tuning completed Inception V3 models were used as feature extractors. A point-binary correlation analysis technique was used to select effective features for classification from the features extracted through the feature extractor. A crystal coefficient value, which is the square of the correlation coefficient value, is used for an accurate comparison between the features. We used an artificial neural network as a classifier in this experiment. Fine-tuned Inception V3 has an average accuracy of 87.7%. When 5-fold class validation is advanced by selecting the top 30 characteristics with high crystal coefficient values, the accuracy is 97.5%. These results can greatly assist physicians trying to detect a systolic murmur.","PeriodicalId":282243,"journal":{"name":"2020 International Conference on Information and Communication Technology Convergence (ICTC)","volume":"54 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127580644","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
Research on Plug-and-Play Twin-Field Quantum Key Distribution 即插即用双场量子密钥分发研究
2020 International Conference on Information and Communication Technology Convergence (ICTC) Pub Date : 2020-10-21 DOI: 10.1109/ICTC49870.2020.9289265
C. Park, M. Woo, B. Park, Yong-Su Kim, Sangin Kim, Sang-Wook Han
{"title":"Research on Plug-and-Play Twin-Field Quantum Key Distribution","authors":"C. Park, M. Woo, B. Park, Yong-Su Kim, Sangin Kim, Sang-Wook Han","doi":"10.1109/ICTC49870.2020.9289265","DOIUrl":"https://doi.org/10.1109/ICTC49870.2020.9289265","url":null,"abstract":"In this paper, we have proposed a plug-and-play twin-field quantum key distribution scheme that has passive mode-matching characteristics of quantum signals and can be operated stably. Also, we have experimentally demonstrated the implementation feasibility of our proposed scheme.","PeriodicalId":282243,"journal":{"name":"2020 International Conference on Information and Communication Technology Convergence (ICTC)","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133126260","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
An Experimental Study on Reinforcement Learning on IoT Devices with Distilled Knowledge 基于知识提炼的物联网设备强化学习实验研究
2020 International Conference on Information and Communication Technology Convergence (ICTC) Pub Date : 2020-10-21 DOI: 10.1109/ICTC49870.2020.9289526
Ingook Jang, Seonghyun Kim, Hyunseok Kim, Chan-Won Park, Jun Hee Park
{"title":"An Experimental Study on Reinforcement Learning on IoT Devices with Distilled Knowledge","authors":"Ingook Jang, Seonghyun Kim, Hyunseok Kim, Chan-Won Park, Jun Hee Park","doi":"10.1109/ICTC49870.2020.9289526","DOIUrl":"https://doi.org/10.1109/ICTC49870.2020.9289526","url":null,"abstract":"This paper provides an experimental study of reinforcement learning on IoT devices using distilled knowledge, whose a teacher with a well-trained model transfers to a student with a new model to be trained. The experimental results show that the distilled knowledge is effective to a new model training on IoT devices.","PeriodicalId":282243,"journal":{"name":"2020 International Conference on Information and Communication Technology Convergence (ICTC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133210744","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 2
Wireless Energy Harvesting IC for Low Power IoT sensor 用于低功耗物联网传感器的无线能量采集IC
2020 International Conference on Information and Communication Technology Convergence (ICTC) Pub Date : 2020-10-21 DOI: 10.1109/ICTC49870.2020.9289078
Jin-sup Kim
{"title":"Wireless Energy Harvesting IC for Low Power IoT sensor","authors":"Jin-sup Kim","doi":"10.1109/ICTC49870.2020.9289078","DOIUrl":"https://doi.org/10.1109/ICTC49870.2020.9289078","url":null,"abstract":"A CMOS wireless energy harvesting IC is designed and fabricated for low power IoT sensor. A small single wireless energy harvester including dynamic power switch, ramp oscillator and DC-DC boost up converter is presented. It is consist of two blocks; one is a dynamic power switch, and the other is a DC-DC boost up converter with low power ramp oscillator. The dynamic power switch monitoring the voltage of off-chip storage capacitor (Vcap). When Vcap is higher than turn on voltage (Vin1), dynamic power switch is turned on then discharges the Vcap. Otherwise, when Vcap decreased lower than turn off voltage (Vin2), the dynamic power switch is turn off. The wireless energy harvesting circuit has been designed using a 0.18-μm HV (High Voltage) CMOS technology and its die chip size is a 1.17 mm × 1.17 mm. The DC-DC boost up converter can increase Vcap up to 5.5 V for charging the battery. Also, it consumes about 10 mA (max) supply current at 1.8 V.","PeriodicalId":282243,"journal":{"name":"2020 International Conference on Information and Communication Technology Convergence (ICTC)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133413560","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 2
Sound Event Detection in Cowshed using Synthetic Data and Convolutional Neural Network 基于合成数据和卷积神经网络的牛棚声事件检测
2020 International Conference on Information and Communication Technology Convergence (ICTC) Pub Date : 2020-10-21 DOI: 10.1109/ICTC49870.2020.9289545
Yagya Raj Pandeya, Bhuwan Bhattarai, Joonwhoan Lee
{"title":"Sound Event Detection in Cowshed using Synthetic Data and Convolutional Neural Network","authors":"Yagya Raj Pandeya, Bhuwan Bhattarai, Joonwhoan Lee","doi":"10.1109/ICTC49870.2020.9289545","DOIUrl":"https://doi.org/10.1109/ICTC49870.2020.9289545","url":null,"abstract":"The sound event detection is a reasonable choice for several application domains like cattle shed, dense forest, or any dark environment where the visual object usually obscured or unseen. The aim of this study is the development of an autonomous monitoring system for welfare management in large cow farms based on sound characteristics. In this paper, we prepare a cow sound artificial dataset and develop a sound event annotation tool for annotation of data. We propose a convolutional neural network (CNN) architecture for rare sound event detection. The applied object detection method achieves a higher quantitative evaluation score and a more precise qualitative result than the past related study. Finally, we conclude that the CNN based architecture for rare sound object detection can be one solution for domestic welfare management. Indeed, the artificial data preparation strategy can be a way to deal with the data scarcity problem and annotation difficulties for rare sound event detection.","PeriodicalId":282243,"journal":{"name":"2020 International Conference on Information and Communication Technology Convergence (ICTC)","volume":"142 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133929519","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 9
Design and Implementation of Packet Filtering Module for Vehicular Multi-domain Network 车载多域网络包过滤模块的设计与实现
2020 International Conference on Information and Communication Technology Convergence (ICTC) Pub Date : 2020-10-21 DOI: 10.1109/ICTC49870.2020.9289459
Joongyong Choi, Boheung Jung
{"title":"Design and Implementation of Packet Filtering Module for Vehicular Multi-domain Network","authors":"Joongyong Choi, Boheung Jung","doi":"10.1109/ICTC49870.2020.9289459","DOIUrl":"https://doi.org/10.1109/ICTC49870.2020.9289459","url":null,"abstract":"In-vehicle networks are changing into structures that form individual domains according to their roles. Furthermore, domain gateways are being introduced to connect each domain, and the need for a security function through this device is raised. Therefore, we propose a packet filtering technique suitable for a vehicle multi-domain gateway.","PeriodicalId":282243,"journal":{"name":"2020 International Conference on Information and Communication Technology Convergence (ICTC)","volume":"25 1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133938710","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Single Image Super Resolution Using Convolutional Neural Networks for Noisy Images 使用卷积神经网络处理噪声图像的单图像超分辨率
2020 International Conference on Information and Communication Technology Convergence (ICTC) Pub Date : 2020-10-21 DOI: 10.1109/ICTC49870.2020.9289414
Tae Bok Lee, Y. S. Heo
{"title":"Single Image Super Resolution Using Convolutional Neural Networks for Noisy Images","authors":"Tae Bok Lee, Y. S. Heo","doi":"10.1109/ICTC49870.2020.9289414","DOIUrl":"https://doi.org/10.1109/ICTC49870.2020.9289414","url":null,"abstract":"In this paper, we address a problem of image super resolution to obtain a noise-free and high resolution image from a noisy and low resolution image. In recent years, deep learning-based approaches have been achieved a lot of progress to the image restoration problems. However, it is still not trivial to generate a high quality image when the input image is both noisy and low-resolution, because it is difficult to disambiguate the fine texture components from noise components for the input image. In this case, conventional super-resolution algorithms usually amplify the noise along with the details. To deal with this problem, we propose a super-resolution network that is robust to noisy images by constructing multi-modules in parallel architecture. The experimental results show that our proposed network restores a noise-free and rich-texture image from the low-resolution and noisy input image, while other methods fail.","PeriodicalId":282243,"journal":{"name":"2020 International Conference on Information and Communication Technology Convergence (ICTC)","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131771726","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 2
A Method for Optimizing Deep Learning Object Detection in Edge Computing 一种优化边缘计算中深度学习目标检测的方法
2020 International Conference on Information and Communication Technology Convergence (ICTC) Pub Date : 2020-10-21 DOI: 10.1109/ICTC49870.2020.9289529
Ryangsoo Kim, Geonyong Kim, Heedo Kim, Giha Yoon, Hark Yoo
{"title":"A Method for Optimizing Deep Learning Object Detection in Edge Computing","authors":"Ryangsoo Kim, Geonyong Kim, Heedo Kim, Giha Yoon, Hark Yoo","doi":"10.1109/ICTC49870.2020.9289529","DOIUrl":"https://doi.org/10.1109/ICTC49870.2020.9289529","url":null,"abstract":"Recently, edge computing has received considerable attention as a promising solution to provide deep learning-based video analysis services in real-time. However, due to the limited computation capability of the data processing units (such as CPUs, GPUs, and specialized accelerators) embedded in the edge devices, the question of how to use the limited resources of the edge devices is one of the most pressing issues affecting deep learning-based video analysis service efficiency. In this paper, we introduce a practical approach to optimize deep learning object detection at the edge devices embedding CPUs and GPUs. The proposed approach adopts TVM, an automated end-to-end deep learning compiler that automatically optimizes deep learning workloads with respect to hardware-specific characteristics. In addition, task-level pipeline parallelism is applied to maximize resource utilization of the CPUs and GPUs so as to improve overall object detection performance. Through experiment results, we show that the proposed approach achieves performance improvement for detecting objects on multiple video streams in terms of frame per second.","PeriodicalId":282243,"journal":{"name":"2020 International Conference on Information and Communication Technology Convergence (ICTC)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134057696","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 5
De-identification and restoration methods for protecting privacy in off-line documents 保护离线文档隐私的去识别和恢复方法
2020 International Conference on Information and Communication Technology Convergence (ICTC) Pub Date : 2020-10-21 DOI: 10.1109/ICTC49870.2020.9289156
Jin-Hee Han, Young-Sae Kim, G. Kim
{"title":"De-identification and restoration methods for protecting privacy in off-line documents","authors":"Jin-Hee Han, Young-Sae Kim, G. Kim","doi":"10.1109/ICTC49870.2020.9289156","DOIUrl":"https://doi.org/10.1109/ICTC49870.2020.9289156","url":null,"abstract":"The necessity of protecting personal information contained in off-line documents (e.g., identification cards, driver's licenses, passports, and delivery invoices) is increasing as the subject of privacy is expanding to various objects in the physical world from the existing security perspective, which was limited only to on-line services. In this paper, we propose off-line document protection technology that can safely protect ID cards and important confidential documents released with personal information exposed on the website, and prevent cases where personal information (name, address, phone number, etc.) on delivery and mail is leaked and abused in the crime. The proposed method consists of masking and unmasking process using two-dimensional bar codes and a user’s secret keys. Through the experimental results using the proposed method, we confirmed that personal information in off-line documents can be changed as an unreadable form and that only authorized user can restore the unrecognizable area to prevent the leakage of personal information.","PeriodicalId":282243,"journal":{"name":"2020 International Conference on Information and Communication Technology Convergence (ICTC)","volume":"63 7-8","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114016918","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Data Stream Management for Distributed Devices in Smart Factory 智能工厂分布式设备的数据流管理
2020 International Conference on Information and Communication Technology Convergence (ICTC) Pub Date : 2020-10-21 DOI: 10.1109/ICTC49870.2020.9289625
Y. Lee, Junwook Lee, Seung‐Jun Lee, Daesub Yoon
{"title":"Data Stream Management for Distributed Devices in Smart Factory","authors":"Y. Lee, Junwook Lee, Seung‐Jun Lee, Daesub Yoon","doi":"10.1109/ICTC49870.2020.9289625","DOIUrl":"https://doi.org/10.1109/ICTC49870.2020.9289625","url":null,"abstract":"The distributed smart factory platform provides an environment where various devices deployed in the factory can perform intelligent collaboration while horizontally interacting with the devices around them. This requires individual devices to be able to process and manage their own data stream collected in the shop floor. In this paper, we focus on building a system for efficiently managing data generated in a smart factory environment, and propose a data stream management structure to support it. In the proposed approach, sliding window and continuous query processing mechanisms are introduced to immediately process various types of data stream collected from devices at the time of occurrence. In addition, we propose a strategy to store processed historical data in local database by introducing temporal approach.","PeriodicalId":282243,"journal":{"name":"2020 International Conference on Information and Communication Technology Convergence (ICTC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115599990","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
首页 上一页
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整，为了账户安全，请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
请完成安全验证×
相关产品
×
本文献相关产品
联系我们：info@booksci.cn Book学术提供免费学术资源搜索服务，方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号：604180095
Book学术官方微信