发布求助
文献互助 智能选刊 最新文献

2018 4th Annual International Conference on Network and Information Systems for Computers (ICNISC)最新文献

筛选
英文 中文
Adaptive Detection of Infrared Small Target Based on Target-Background Separation with Ratio Minimization of Singular Values 基于奇异值比最小化的目标背景分离红外小目标自适应检测
2018 4th Annual International Conference on Network and Information Systems for Computers (ICNISC) Pub Date : 2018-04-19 DOI: 10.1109/ICNISC.2018.00036
Yu-Yuan Yang, Wei-Dong Sun
{"title":"Adaptive Detection of Infrared Small Target Based on Target-Background Separation with Ratio Minimization of Singular Values","authors":"Yu-Yuan Yang, Wei-Dong Sun","doi":"10.1109/ICNISC.2018.00036","DOIUrl":"https://doi.org/10.1109/ICNISC.2018.00036","url":null,"abstract":"Motivated by the infrared patch-image model, small target detection is transformed into an optimization problem of the low-rank and sparse matrix decomposition. Previous methods may have unstable performance when faced with extremely complex backgrounds with strong edges and dim targets. Thus, a new adaptive detection method for infrared small target using multi-scale fusion and parameter regulation is proposed, based on the non-negative target assumption and the ratio between partial and total sum of background singular values. The parameters for target-background separation are regulated adaptively using the image entropy and the standard deviation of image patches. A series of experiments shows that our proposed method has an excellent and stable performance in background clutter suppression, especially in extremely variant and complex backgrounds, and is more accurate with low false alarm rate compared with other baseline methods.","PeriodicalId":263400,"journal":{"name":"2018 4th Annual International Conference on Network and Information Systems for Computers (ICNISC)","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-04-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126065768","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: 6
Long-term Tracking Based on Kernelized Correlation Filtering 基于核相关滤波的长期跟踪
2018 4th Annual International Conference on Network and Information Systems for Computers (ICNISC) Pub Date : 2018-04-01 DOI: 10.1109/ICNISC.2018.00041
Wu Qiang, Zhou Zheng
{"title":"Long-term Tracking Based on Kernelized Correlation Filtering","authors":"Wu Qiang, Zhou Zheng","doi":"10.1109/ICNISC.2018.00041","DOIUrl":"https://doi.org/10.1109/ICNISC.2018.00041","url":null,"abstract":"Aiming at the problems of kernelized correlation filter tracking algorithm such as scale change, severe occlusion and tracking failure under similar target tracking, a long-term target tracking algorithm based on KCF is proposed. The algorithm introduces color information into the tracker, and the scale information makes the algorithm adapt to the more complex situation when tracking. It is worth noting that the trackers train two models, one to represent coordinates and the other to characterize confidence. In addition, training online support vector machine classifiers is also crucial. This article uses a multi-expert tracking strategy to enable longterm tracking to be re-detected in the event of a failed tracking condition. The validity of the proposed algorithm is verified by the OTB-2013 [1] evaluation sequence. Compared with several other classical algorithms, this algorithm has been significantly improved. In the target occurrence scale, occlusion, deformation and other interference cases with strong robustness.","PeriodicalId":263400,"journal":{"name":"2018 4th Annual International Conference on Network and Information Systems for Computers (ICNISC)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117051672","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: 3
Research on the Method of Finding the Semantic Relationship of Datasets 数据集语义关系查找方法研究
2018 4th Annual International Conference on Network and Information Systems for Computers (ICNISC) Pub Date : 2018-04-01 DOI: 10.1109/ICNISC.2018.00065
Gong Zhen, Fan Bing bing
{"title":"Research on the Method of Finding the Semantic Relationship of Datasets","authors":"Gong Zhen, Fan Bing bing","doi":"10.1109/ICNISC.2018.00065","DOIUrl":"https://doi.org/10.1109/ICNISC.2018.00065","url":null,"abstract":"In order to programmatically discover semantic associations between datasets, promote open sharing of linked data. In this paper, a description model of relational datasets is designed, and a datasets association detection method based on semantic similarity is proposed based on the characteristics of datasets. The experiment shows that this study can not only realize the correlation of the basic description level of the datasets, but also find the semantic association between the entities in the datasets. This method can realize the semantic interconnection across datasets, to improve the relevance of data and information.","PeriodicalId":263400,"journal":{"name":"2018 4th Annual International Conference on Network and Information Systems for Computers (ICNISC)","volume":"109 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128113978","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
Application of Test Case Selection and Fault Analysis Based on Orthogonal Experiment in Mobile Device Context-Aware Application Testing 基于正交试验的测试用例选择与故障分析在移动设备上下文感知应用测试中的应用
2018 4th Annual International Conference on Network and Information Systems for Computers (ICNISC) Pub Date : 2018-04-01 DOI: 10.1109/ICNISC.2018.00099
Yang Guo, Lu Lu
{"title":"Application of Test Case Selection and Fault Analysis Based on Orthogonal Experiment in Mobile Device Context-Aware Application Testing","authors":"Yang Guo, Lu Lu","doi":"10.1109/ICNISC.2018.00099","DOIUrl":"https://doi.org/10.1109/ICNISC.2018.00099","url":null,"abstract":"With the rapid development of mobile devices and the advent and application of various sensors, a large number of context-aware applications have emerged. As more and more contextual information is available for these applications, the functions implemented are becoming more complex. Due to the variety of contextual information, the design of test cases requires very complicated combination of conditions, which greatly increases the difficulty of software testing. This paper proposes a test case selection method based on orthogonal experiment design, which greatly reduces the number of test cases under the premise of ensuring effective coverage, and at the same time, the method also has the ability of error location. The experimental results show that the test cases designed by this method are evenly distributed and show good comprehensiveness. By separating the influence of each independent factor, it is helpful to find out the influencing factors of fault detection rate and thus locate the fault.","PeriodicalId":263400,"journal":{"name":"2018 4th Annual International Conference on Network and Information Systems for Computers (ICNISC)","volume":"82 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125670126","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
Recommend Device Defect Research Based on Optimized Edit Distance Algorithm and Entropy Weight Method 基于优化编辑距离算法和熵权法的推荐设备缺陷研究
2018 4th Annual International Conference on Network and Information Systems for Computers (ICNISC) Pub Date : 2018-04-01 DOI: 10.1109/ICNISC.2018.00068
Qi Jing-Xian, Jiang Yu
{"title":"Recommend Device Defect Research Based on Optimized Edit Distance Algorithm and Entropy Weight Method","authors":"Qi Jing-Xian, Jiang Yu","doi":"10.1109/ICNISC.2018.00068","DOIUrl":"https://doi.org/10.1109/ICNISC.2018.00068","url":null,"abstract":"This paper proposes a defect recommendation method based on an optimized edit distance algorithm and entropy weight method. The connection between the production management system (PMS) and the operation management system (OMS) need they choose defects personally, which results in staff workload increased significantly and data interact unreasonably. Firstly, the optimized edit distance algorithm is being used for classifying defects identification, and then use entropy weight method to evaluate the type, in order to achieve the intelligent recommendation to relevant personnel. The experimental results show that the implementation of the proposed method greatly reduces the workload of the relevant personnel, and improves the accuracy of the defect information recommendation.","PeriodicalId":263400,"journal":{"name":"2018 4th Annual International Conference on Network and Information Systems for Computers (ICNISC)","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115881092","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
Survey of Kernel Extreme Learning Machine Kernel Function Based on the Perspective of Kernel Parameter Optimization Time 基于核参数优化时间视角的核极限学习机核函数研究
2018 4th Annual International Conference on Network and Information Systems for Computers (ICNISC) Pub Date : 2018-04-01 DOI: 10.1109/ICNISC.2018.00093
Sen-Yue Zhang, Wen-An Tan, Yi-bo Li
{"title":"Survey of Kernel Extreme Learning Machine Kernel Function Based on the Perspective of Kernel Parameter Optimization Time","authors":"Sen-Yue Zhang, Wen-An Tan, Yi-bo Li","doi":"10.1109/ICNISC.2018.00093","DOIUrl":"https://doi.org/10.1109/ICNISC.2018.00093","url":null,"abstract":"The Kernel Extreme Learning Machine (KELM) is more and more widely used in various fields, and the factor that determines the performance of KELM is the selected kernel function. The kernel functions are divided into two common types in this paper: the kernel inner product functions and kernel functions based on orthogonal polynomials that only require values in natural numbers. From the perspective of kernel parameter optimization time, the current research status and development of the above kernel functions are systematically summarized, which provided relevant researchers with the development history and latest results of the research direction.","PeriodicalId":263400,"journal":{"name":"2018 4th Annual International Conference on Network and Information Systems for Computers (ICNISC)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123499496","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
DOA Estimation of Nested Electromagnetic Vector Sensors Array via MUSIC Algorithm 基于MUSIC算法的嵌套电磁矢量传感器阵列DOA估计
2018 4th Annual International Conference on Network and Information Systems for Computers (ICNISC) Pub Date : 2018-04-01 DOI: 10.1109/ICNISC.2018.00066
Xinping Lin, Meng-Jie Zhou, Lang He, Chao Ge, Xiao-fei Zhang
{"title":"DOA Estimation of Nested Electromagnetic Vector Sensors Array via MUSIC Algorithm","authors":"Xinping Lin, Meng-Jie Zhou, Lang He, Chao Ge, Xiao-fei Zhang","doi":"10.1109/ICNISC.2018.00066","DOIUrl":"https://doi.org/10.1109/ICNISC.2018.00066","url":null,"abstract":"In this paper, we propose the idea of combining the nested array with the electromagnetic vector sensor to achieve the spatial spectrum estimation. The subspace algorithm of (Multiple signal classification) MUSIC algorithm is applied to the Direction of Arrival (DOA) estimation, and the spatial smoothing technique is utilized to the covariance matrix of virtual received signal here so that its rank can be restored. Compared with the uniform scalar sensor array, the proposed method has higher angle estimation performance and higher spatial Degree of Freedom (DOF). Through a nested array of only N physical sensors, O(6N2) DOFs is obtained. Otherwise, the angle estimation performance of a vector sensors array is better than the scalar sensors array.","PeriodicalId":263400,"journal":{"name":"2018 4th Annual International Conference on Network and Information Systems for Computers (ICNISC)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130449833","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: 3
Research on Modeling of User Learning Interest Based on Evolutionary Computation 基于进化计算的用户学习兴趣建模研究
2018 4th Annual International Conference on Network and Information Systems for Computers (ICNISC) Pub Date : 2018-04-01 DOI: 10.1109/ICNISC.2018.00062
Feng Dong-hua, Li Meng
{"title":"Research on Modeling of User Learning Interest Based on Evolutionary Computation","authors":"Feng Dong-hua, Li Meng","doi":"10.1109/ICNISC.2018.00062","DOIUrl":"https://doi.org/10.1109/ICNISC.2018.00062","url":null,"abstract":"Evolutionary computation is a computing discipline that mimics biological evolution and genetic laws. In order to realize the modeling of the user's interest in learning, an Evolutionary Computation Based Modeling (ECBM) method is proposed. The method uses a genetic algorithm to model the user's interest in learning and automatically evolves the model parameters. User interest modeling is the foundation and core of personalized learning.","PeriodicalId":263400,"journal":{"name":"2018 4th Annual International Conference on Network and Information Systems for Computers (ICNISC)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121068594","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
Doppler Frequency Offset Estimation Algorithm for Terahertz Dynamic Imaging Signal 太赫兹动态成像信号的多普勒频偏估计算法
2018 4th Annual International Conference on Network and Information Systems for Computers (ICNISC) Pub Date : 2018-04-01 DOI: 10.1109/ICNISC.2018.00037
Xiang Jun-Zi
{"title":"Doppler Frequency Offset Estimation Algorithm for Terahertz Dynamic Imaging Signal","authors":"Xiang Jun-Zi","doi":"10.1109/ICNISC.2018.00037","DOIUrl":"https://doi.org/10.1109/ICNISC.2018.00037","url":null,"abstract":"Terahertz Imaging promotes microscopic dialysis and deep utilization of electromagnetic wave, and provides significant foundation for exploiting microscopic and high frequency object while challenges as channel interference and Doppler frequency Offset of dynamic signal are still urgent to be solved. Hence, this article comes up with Doppler frequency Offset estimation algorithm for Terahertz dynamic Imaging signal. This article starts from analysing signal model and channel influence of Terahertz Imaging, further proposing feature analyses for signal interference in imaging channel, and ends in implementing radio frequency and baseband of the receiver. A handling method is designed for Doppler frequency Offset of received dynamic signal and it can validly compensate Doppler frequency Offset of dynamic signal. The simulation proves that the algorithm in this article can improve estimation accuracy of Doppler frequency Offset in Terahertz Imaging.","PeriodicalId":263400,"journal":{"name":"2018 4th Annual International Conference on Network and Information Systems for Computers (ICNISC)","volume":"98 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124351923","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
Distortion Correction of Building-Fisheye-Images 建筑物-鱼眼图像的畸变校正
2018 4th Annual International Conference on Network and Information Systems for Computers (ICNISC) Pub Date : 2018-04-01 DOI: 10.1109/ICNISC.2018.00044
Su Jie, Jiang Dong-qi, Wang Xu-guang
{"title":"Distortion Correction of Building-Fisheye-Images","authors":"Su Jie, Jiang Dong-qi, Wang Xu-guang","doi":"10.1109/ICNISC.2018.00044","DOIUrl":"https://doi.org/10.1109/ICNISC.2018.00044","url":null,"abstract":"The fisheye image is the image taken with a fisheye camera, in which the object suffer from distortion. The street view building images are always taken by fisheye cameras due to the boarder view of the very cameras. So, the distortion of the images must be corrected before further applications. This paper compared three state of the art's distortion correction algorithms, including algorithm based on Polynomial Model, algorithm based on Division Model, and algorithm in [1]. The comparison results on both synthetic and real data show that algorithm in [1] performs the best.","PeriodicalId":263400,"journal":{"name":"2018 4th Annual International Conference on Network and Information Systems for Computers (ICNISC)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121974252","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
下一页 尾页
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
小红书