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Ensemble Deep Network for Dense Vehicle Detection in Large Image 基于集成深度网络的大图像密集车辆检测
Pub Date : 2021-01-01 DOI: 10.9708/JKSCI.2021.26.01.045
Jae-Hyoung Yu, Youngjoon Han, Jongkuk Kim, H. Hahn
[Abstract] This paper has proposed an algorithm that detecting for dense small vehicle in large image efficiently. It is consisted of two Ensemble Deep-Learning Network algorithms based on Coarse to Fine method. The system can detect vehicle exactly on selected sub image. In the Coarse step, it can make Voting Space using the result of various Deep-Learning Network individually. To select sub-region, it makes Voting Map by to combine each Voting Space. In the Fine step, the sub-region selected in the Coarse step is transferred to final Deep-Learning Network. The sub-region can be defined by using dynamic windows. In this paper, pre-defined mapping table has used to define dynamic windows for perspective road image. Identity judgment of vehicle moving on each sub-region is determined by closest center point of bottom of the detected vehicle's box information. And it is tracked by vehicle's box information on the continuous images. The proposed algorithm has evaluated for performance of detection and cost in real time using day and night images captured by CCTV on the road.
[摘要]本文提出了一种对大图像中密集小型车辆进行高效检测的算法。它由两种基于粗变细方法的集成深度学习网络算法组成。该系统可以对选定的子图像进行准确的车辆检测。在粗化步骤中,可以分别利用各种深度学习网络的结果来构造投票空间。为了选择子区域,将每个投票空间组合成投票地图。在精细步骤中,将粗步中选择的子区域转移到最终的深度学习网络中。子区域可以通过使用动态窗口来定义。本文使用预定义映射表来定义透视道路图像的动态窗口。在每个子区域上移动的车辆的身份判断是由被检测车辆箱体信息的最底部中心点确定的。并通过连续图像上的车辆箱体信息进行跟踪。利用CCTV在道路上捕获的日夜图像,对该算法的检测性能和成本进行了实时评估。
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引用次数: 0
Secure Training Support Vector Machine with Partial Sensitive Part 部分敏感部件的安全训练支持向量机
Pub Date : 2021-01-01 DOI: 10.9708/JKSCI.2021.26.04.001
Saerom Park
In this paper, we propose a training algorithm of support vector machine (SVM) with a sensitive variable. Although machine learning models enable automatic decision making in the real world applications, regulations prohibit sensitive information from being used to protect privacy. In particular, the privacy protection of the legally protected attributes such as race, gender, and disability is compulsory. We present an efficient least square SVM (LSSVM) training algorithm using a fully homomorphic encryption (FHE) to protect a partial sensitive attribute. Our framework posits that data owner has both non-sensitive attributes and a sensitive attribute while machine learning service provider (MLSP) can get non-sensitive attributes and an encrypted sensitive attribute. As a result, data owner can obtain the encrypted model parameters without exposing their sensitive information to MLSP. In the inference phase, both non-sensitive attributes and a sensitive attribute are encrypted, and all computations should be conducted on encrypted domain. Through the experiments on real data, we identify that our proposed method enables to implement privacy-preserving sensitive LSSVM with FHE that has comparable performance with the original LSSVM algorithm. In addition, we demonstrate that the efficient sensitive LSSVM with FHE significantly improves the computational cost with a small degradation of performance.
本文提出了一种带有敏感变量的支持向量机训练算法。虽然机器学习模型可以在现实世界的应用程序中实现自动决策,但法规禁止使用敏感信息来保护隐私。特别是对种族、性别、残疾等受法律保护的属性的隐私保护是强制性的。提出了一种利用全同态加密(FHE)保护部分敏感属性的高效最小二乘支持向量机(LSSVM)训练算法。我们的框架假设数据所有者同时具有非敏感属性和敏感属性,而机器学习服务提供商(MLSP)可以获得非敏感属性和加密的敏感属性。因此,数据所有者可以在不将其敏感信息暴露给MLSP的情况下获得加密的模型参数。在推理阶段,对非敏感属性和敏感属性进行加密,所有计算都在加密域上进行。通过对真实数据的实验,我们发现我们的方法能够实现具有FHE的隐私保护敏感LSSVM,并且具有与原始LSSVM算法相当的性能。此外,我们还证明了具有FHE的高效敏感LSSVM在性能下降很小的情况下显着提高了计算成本。
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引用次数: 0
A study on non-face-to-face 5AL teaching and learning method applying extended reality (XR) 应用扩展现实(XR)的非面对面5AL教与学方法研究
Pub Date : 2021-01-01 DOI: 10.9708/JKSCI.2021.26.09.125
B. Lee, Kyoung-A Lee
Abstract
摘要
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引用次数: 0
A Study on Digital Healthcare Optometry System Using Optometry DB 基于验光数据库的数字医疗验光系统研究
Pub Date : 2021-01-01 DOI: 10.9708/JKSCI.2021.26.09.155
Do-yeon Kim, J. Jung, Yong-Man Kim, Koo-Rack Park
[Abstract] Recently, digital health care technology is spreading and developing in various fields. Therefore, in this paper, we realized that the field to which digital healthcare technology is not applied is the field of optometry, and implemented a digital healthcare optometry system for precise lens manufacturing. A device called Phoroptor is used to manufacture the lens, and this device sets the lens by measuring the visual acuity of the person who requested the glasses. And when the person to be measured wears glasses, a device called a PD meter is used to align the pupil center and lens focus. However, there is a limit to the convenience of precise lens production and optometry due to the absence of a database and program that can accumulate and analyze the PD measurement error, inconvenience and error due to manual control of the Phoroptor, and optometric information. Therefore, in this paper, PD meter design for more accurate PD measurement, Phoroptor design and Phoroptor control application design for automatic Phoroptor control, and a database and analysis program that automatically set lenses using optometry information for each subject had been designed. Based on this, ultimately, a digital healthcare optometry system using an optometry database has been implemented.
【摘要】近年来,数字医疗技术在各个领域得到推广和发展。因此,在本文中,我们意识到数字医疗技术无法应用的领域是验光领域,并实现了用于精密镜片制造的数字医疗验光系统。一种叫做Phoroptor的设备被用来制造镜片,该设备通过测量要求佩戴眼镜的人的视力来设置镜片。当被测者戴上眼镜时,一种被称为PD计的设备被用来校准瞳孔中心和透镜焦点。然而,由于缺乏一个数据库和程序来积累和分析PD测量误差,由于人工控制phooptor带来的不便和误差,以及验光信息,限制了精密镜片生产和验光的便利性。因此,本文设计了实现更精确PD测量的PD计设计、实现自动光控的Phoroptor设计和Phoroptor控制应用程序设计,以及根据每个被试的验光信息自动设置镜头的数据库和分析程序。在此基础上,最终实现了使用验光数据库的数字医疗验光系统。
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引用次数: 0
The Possibility of Neural Network Approach to Solve Singular Perturbed Problems 神经网络方法求解奇异摄动问题的可能性
Pub Date : 2021-01-01 DOI: 10.9708/JKSCI.2021.26.01.069
Jee-Hyun Kim, Young-Im Cho
Recentlly neural network approach for solving a singular perturbed integro-differential boundary value problem have been researched. Especially the model of the feed-forward neural network to be trained by the back propagation algorithm with various learning algorithms were theoretically substantiated, and neural network models such as deep learning, transfer learning, federated learning are very rapidly evolving. The purpose of this paper is to study the approaching method for developing a neural network model with high accuracy and speed for solving singular perturbed problem along with asymptotic methods. In this paper, we propose a method that the simulation for the difference between result value of singular perturbed problem and unperturbed problem by using neural network approach equation. Also, we showed the efficiency of the neural network approach. As a result, the contribution of this paper is to show the possibility of simple neural network approach for singular perturbed problem solution efficiently.
近年来研究了求解奇异摄动积分微分边值问题的神经网络方法。特别是用反向传播算法训练的前馈神经网络模型与各种学习算法在理论上得到了证实,深度学习、迁移学习、联邦学习等神经网络模型的发展非常迅速。本文的目的是研究用渐近方法建立求解奇异摄动问题的高精度、快速的神经网络模型的逼近方法。本文提出了一种用神经网络逼近方程模拟奇异摄动问题与非摄动问题结果值之差的方法。此外,我们还展示了神经网络方法的有效性。因此,本文的贡献在于展示了简单神经网络方法有效求解奇异摄动问题的可能性。
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引用次数: 0
Design of an Exploration Drone for Digital Twin based Building Control 基于数字孪生体的建筑控制探索无人机设计
Pub Date : 2021-01-01 DOI: 10.9708/JKSCI.2021.26.05.009
Sang-hoon Shin, Myeong-Chul Park
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引用次数: 0
Effects of an Aquatic Exercise Program on Body Composition, Blood Components and Physical Fitness in the Elderly Women 水上运动对老年妇女身体成分、血液成分和体质的影响
Pub Date : 2021-01-01 DOI: 10.9708/JKSCI.2021.26.08.075
Soon-Hee Lee, I. Yang
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引用次数: 0
Educational Contents for Concepts and Algorithms of Artificial Intelligence 人工智能的概念和算法教学内容
Pub Date : 2021-01-01 DOI: 10.9708/JKSCI.2021.26.01.037
Han Sun Gwan
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引用次数: 1
Canonical correlation between body information and lipid-profile: A study on the National Health Insurance Big Data in Korea 体质信息与血脂的典型相关性:韩国国民健康保险大数据研究
Pub Date : 2021-01-01 DOI: 10.9708/JKSCI.2021.26.01.201
Han-Gue Jo, Young-Heung Kang
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引用次数: 0
A Study on Satisfaction of Third Party Mobile Payment Service in China 中国第三方移动支付服务满意度研究
Pub Date : 2021-01-01 DOI: 10.9708/JKSCI.2021.26.01.259
Jae-Young Moon
[Abstract] SNS has recently reached the level of providing financial services to customers through a mobile payment system that goes beyond the existing payment system using Fintech, which is a fusion of financial industry and information technology. These mobile payment systems are increasing in scale as time goes by, and their functions are reaching the same level as general financial services. This study is an empirical study to examine what is the most important factor in Internet banking by targeting users who use WeChat Pay among Chinese Internet bank users with the highest Fintech Adoption rate. SNS has recently reached the level of providing financial services to customers through a mobile payment system that goes beyond the existing payment system using Fintech, which is a fusion of financial industry and information technology. As a results, 2 factors positive influence on Acceptance intention and Customer satisfaction. These mobile payment systems are increasing in scale as time goes by, and their functions are reaching the same level as general financial services.
【摘要】最近,SNS已经达到了通过移动支付系统向客户提供金融服务的水平,这种移动支付系统超越了现有的使用Fintech的支付系统,是金融行业与信息技术的融合。随着时间的推移,这些移动支付系统的规模越来越大,其功能已达到与一般金融服务相同的水平。本研究是一项实证研究,以金融科技采用率最高的中国互联网银行用户中使用微信支付的用户为目标,研究互联网银行最重要的因素是什么。SNS最近利用金融产业和信息技术(it)的融合——金融科技(Fintech),超越了现有的支付系统,通过移动支付系统向顾客提供金融服务。结果表明,2个因素对接受意向和顾客满意度有正向影响。随着时间的推移,这些移动支付系统的规模越来越大,其功能已达到与一般金融服务相同的水平。
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引用次数: 0
期刊
Journal of the Korea Society of Computer and Information
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