2020 IEEE 4th Information Technology, Networking, Electronic and Automation Control Conference (ITNEC)最新文献

Electronic Product Surface Defect Detection Based on a MSSD Network 基于MSSD网络的电子产品表面缺陷检测

2020 IEEE 4th Information Technology, Networking, Electronic and Automation Control Conference (ITNEC) Pub Date : 2020-06-01 DOI: 10.1109/ITNEC48623.2020.9084756

Yong Li, Jinbing Xu

引用次数: 5

Research on Quality Evaluation Technology of “Model Data Platform” for PaaS Layer 面向PaaS层的“模型数据平台”质量评价技术研究

2020 IEEE 4th Information Technology, Networking, Electronic and Automation Control Conference (ITNEC) Pub Date : 2020-06-01 DOI: 10.1109/ITNEC48623.2020.9085224

Ling-lin Gong, Yujia Li, Yuan Cheng, Xin Xu

引用次数: 0

Small sample radar target recognition based on metric learning 基于度量学习的小样本雷达目标识别

2020 IEEE 4th Information Technology, Networking, Electronic and Automation Control Conference (ITNEC) Pub Date : 2020-06-01 DOI: 10.1109/ITNEC48623.2020.9085139

Yuan Yan, Jun Sun, Junpeng Yu, Jingming Sun

{"title":"Small sample radar target recognition based on metric learning","authors":"Yuan Yan, Jun Sun, Junpeng Yu, Jingming Sun","doi":"10.1109/ITNEC48623.2020.9085139","DOIUrl":"https://doi.org/10.1109/ITNEC48623.2020.9085139","url":null,"abstract":"Radar maritime target recognition, not affected by weather and illumination, plays a vital role in sea state detection. But the development of radar ship target recognition has been obstructed due to complicated sea conditions and difficult data acquisition. Traditional recognition methods are difficult to extract robust and highly discriminative features. CNNs is widely used in radar target recognition because of its self-learning. But CNNs has low learning efficiency and poor classification performance under small sample conditions. In this paper, prototype-based metric learning method(PML) is proposed. Specifically, we sample two subsets from original training data as a support set and a query set. The mean of a class's support vectors is calculated to get its centroid in the embedding space, which is called prototype. We find the nearest category prototype for embedded query points to make a classification. It is because our model is more convenient for extracting highly discriminative features and easy to train that it has higher learning efficiency. The experiments is based on Open-SARShip classification dataset in TOPSAR data of the Sentinel-1 satellites for algorithm verification. Experimental results show that recognition accuracy of our model is significantly higher than those achieved by CNNs and traditional radar target recognition models, especially in the limited-data regime.","PeriodicalId":235524,"journal":{"name":"2020 IEEE 4th Information Technology, Networking, Electronic and Automation Control Conference (ITNEC)","volume":"93 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117112878","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

Mitigating Broadcast Storm Problem in VANET when Parked Cars being awaken as Relays 缓解VANET中停车被唤醒为中继时的广播风暴问题

2020 IEEE 4th Information Technology, Networking, Electronic and Automation Control Conference (ITNEC) Pub Date : 2020-06-01 DOI: 10.1109/ITNEC48623.2020.9085081

A. Qiu, Donglin Wang, S. Partani, R. Sattiraju, H. Schotten

{"title":"Mitigating Broadcast Storm Problem in VANET when Parked Cars being awaken as Relays","authors":"A. Qiu, Donglin Wang, S. Partani, R. Sattiraju, H. Schotten","doi":"10.1109/ITNEC48623.2020.9085081","DOIUrl":"https://doi.org/10.1109/ITNEC48623.2020.9085081","url":null,"abstract":"In the urban environment, buildings, moving obstacles usually attenuate signals of safety messages, so that the connectivity and the reliability are reduced, which is known as Obstacle Shadowing problem. A typical solution to address this problem is to deploy Road-Side Units (RSUs), making them relay the Basic Safety Message (BSM) from driving vehicles. However, due to the high cost of deploying RSUs, the large numbers of parked cars in urban areas can be temporally used as RSUs for the financial aspect. Unfortunately, the conventional IEEE 802.11p protocol suffers from a so-called Broadcast Storm problem, where a high rate of contentions and packet collisions occur. In this paper, we show how even a small number of parked cars as relay could cause over 65% loss in Packet Reception Ratio (PRR). Therefore, some broadcast mechanisms are proposed to solve this problem. However, in this paper, we show the limitations of the conventional schemes, and we proposed revised and new schemes for selecting parked cars as relays/RSUs according to their geographic information and the surrounding traffic condition. The benefits are the great reduction in the deployment of RSUs, and significant improvement in the connectivity (up to 60%) and the reliability (up to 70%).","PeriodicalId":235524,"journal":{"name":"2020 IEEE 4th Information Technology, Networking, Electronic and Automation Control Conference (ITNEC)","volume":"117 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117139334","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

A Human Gait Sequence Merging Method For Multi-kinect 一种多体感人体步态序列合并方法

2020 IEEE 4th Information Technology, Networking, Electronic and Automation Control Conference (ITNEC) Pub Date : 2020-06-01 DOI: 10.1109/ITNEC48623.2020.9085205

Xiaojuan He, Chengcheng Chen, Hanzhen Zhang, Yuehu Liu

{"title":"A Human Gait Sequence Merging Method For Multi-kinect","authors":"Xiaojuan He, Chengcheng Chen, Hanzhen Zhang, Yuehu Liu","doi":"10.1109/ITNEC48623.2020.9085205","DOIUrl":"https://doi.org/10.1109/ITNEC48623.2020.9085205","url":null,"abstract":"As a motion capture device, Kinect can predict temporal 3D positions of 25 body joints from depth image, so it is widely used in many field such as gait analysis, gait recognition and clinical medicine. However, the collection range of a single Kinect is very limited and it only collect few gait data, which will greatly reduce the accuracy and reliability of the gait analysis and recognition. In order to solve this problem, we propose a new human gait sequence merging method for multi-Kinect. It can not only extend the data acquisition range and increase the length of gait data sequence, but also avoid the bad effects of walking on a treadmill because it is a non-invasive, non-contact data collection method. Firstly, we first introduced the optimal collection range of kinect to improve the accuracy of gait sequence measurements. Secondly, we directly use the depth value of the joint point for coordinate transformation, which not only reduces the conversion error but also make the calculation easy. Finally, when gait sequences are merged, we utilize all the gait sequences to obtain stable, effective and long-distance gait sequences. We designed relevant experiments to compare the merged gait sequence with the gait sequence collected by single Kinect, and the results verified the validity of the method.","PeriodicalId":235524,"journal":{"name":"2020 IEEE 4th Information Technology, Networking, Electronic and Automation Control Conference (ITNEC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121044658","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

Multi-path interference analysis and simulation of secondary surveillance radar for civil aviation ATC 民航空管二次监视雷达多径干扰分析与仿真

2020 IEEE 4th Information Technology, Networking, Electronic and Automation Control Conference (ITNEC) Pub Date : 2020-06-01 DOI: 10.1109/ITNEC48623.2020.9084696

Xiaojia Yang, Huaicai Zhang, Qiming Luo

引用次数: 3

A Signal Blind Detection Method Based on Wavelet Denoising 基于小波去噪的信号盲检测方法

2020 IEEE 4th Information Technology, Networking, Electronic and Automation Control Conference (ITNEC) Pub Date : 2020-06-01 DOI: 10.1109/ITNEC48623.2020.9084728

Yue Guo, Bin Wang

引用次数: 0

Study on the position of Visual screen in airport constructed End-Around Taxiway 机场环形滑行道可视屏位置的研究

2020 IEEE 4th Information Technology, Networking, Electronic and Automation Control Conference (ITNEC) Pub Date : 2020-06-01 DOI: 10.1109/ITNEC48623.2020.9085137

Bin Yuan, Yuankai Li, Huan Lin, Fei Liang

引用次数: 0

A Performance Degradation Pattern Identification Algorithm based on SPC and Fuzzy Sets for Hydraulic and User Systems 基于SPC和模糊集的液压系统和用户系统性能退化模式识别算法

2020 IEEE 4th Information Technology, Networking, Electronic and Automation Control Conference (ITNEC) Pub Date : 2020-06-01 DOI: 10.1109/ITNEC48623.2020.9085108

Wenyun Yao, Yue Zhao, Cunbao Ma, Guolei Xu, Xu Dong

{"title":"A Performance Degradation Pattern Identification Algorithm based on SPC and Fuzzy Sets for Hydraulic and User Systems","authors":"Wenyun Yao, Yue Zhao, Cunbao Ma, Guolei Xu, Xu Dong","doi":"10.1109/ITNEC48623.2020.9085108","DOIUrl":"https://doi.org/10.1109/ITNEC48623.2020.9085108","url":null,"abstract":"The sensor layout in the hydraulic system of a certain aircraft studied in this paper is less. The flow rate, temperature and other basic parameters related to the recession characteristics of the hydraulic system are not recorded, and there are not many valuable feature parameters directly provided by the existing flight parameters, so the recession characteristics of the relevant system are the primary problem to be solved. Aiming at this problem, we propose a method for constructing performance degradation warning signals based on statistical process control. The known performance degradation warning signal and the constructed performance degradation warning signal constitute a set of regression symptoms. Membership functions are then determined from statistical data on signs and causes of decline combined with expert experience. At the same time, we propose a membership algorithm based on fuzzy multi-attributes to determine the weights of the factors affecting the decline. Finally, the identification matrix is obtained by the comprehensive calculation of the membership of each factor, and then we realize the identification of the decline mode of hydraulic system performance.","PeriodicalId":235524,"journal":{"name":"2020 IEEE 4th Information Technology, Networking, Electronic and Automation Control Conference (ITNEC)","volume":"221 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126040582","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

Research on flame detection algorithm based on multi - feature fusion 基于多特征融合的火焰检测算法研究

2020 IEEE 4th Information Technology, Networking, Electronic and Automation Control Conference (ITNEC) Pub Date : 2020-06-01 DOI: 10.1109/ITNEC48623.2020.9084825

Xipeng Wang, Yong Li, Zhi Li

{"title":"Research on flame detection algorithm based on multi - feature fusion","authors":"Xipeng Wang, Yong Li, Zhi Li","doi":"10.1109/ITNEC48623.2020.9084825","DOIUrl":"https://doi.org/10.1109/ITNEC48623.2020.9084825","url":null,"abstract":"Fast and accurate detection of the flame area in the surveillance video is a necessary condition to reduce the loss caused by fire. This paper combines the dynamic and static features of the flame in the video, and proposes a flame detection method combining the flame color feature and the local feature. Firstly, moving target detection method is used to extract the moving target from video streams, and the effective color segmentation threshold is analyzed and determined. The color threshold is segmented from the two color spaces of RGB and HSV respectively to obtain the suspected flame region. The local features of the target area are extracted, and the feature vector input into the Support Vector Machine classifier for flame detection. The detection effects of the two local features were compared to select the better features. The experiment result shows that the algorithm of this paper achieves the ideal detection effect. Compared with the traditional single feature flame detection method, the algorithm of this paper effectively reduces the impact of the environment on the detection results and reduces the false alarm rate of the fire flame.","PeriodicalId":235524,"journal":{"name":"2020 IEEE 4th Information Technology, Networking, Electronic and Automation Control Conference (ITNEC)","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126132277","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: 8