2021 6th International Conference on Intelligent Computing and Signal Processing (ICSP)最新文献_第5页

Achievable rate-exponent region for parallel distributed detection via binary symmetric channels 可实现的率指数区域并行分布式检测通过二进制对称通道

2021 6th International Conference on Intelligent Computing and Signal Processing (ICSP) Pub Date : 2021-04-09 DOI: 10.1109/ICSP51882.2021.9408679

Xiangyang Liu, Gang Wang, Qiang Wang, Xian Li, Simin Ma

引用次数: 0

A Network Attack Blocking Scheme based on Threat Intelligence 基于威胁情报的网络攻击阻断方案

2021 6th International Conference on Intelligent Computing and Signal Processing (ICSP) Pub Date : 2021-04-09 DOI: 10.1109/ICSP51882.2021.9408916

Kun Li, Rui Wang, Haiwei Li, Yan Hao

{"title":"A Network Attack Blocking Scheme based on Threat Intelligence","authors":"Kun Li, Rui Wang, Haiwei Li, Yan Hao","doi":"10.1109/ICSP51882.2021.9408916","DOIUrl":"https://doi.org/10.1109/ICSP51882.2021.9408916","url":null,"abstract":"In the current network security situation, the types of network threats are complex and changeable. With the development of the Internet and the application of information technology, the general trend is opener. Important data and important business applications will face more serious security threats. However, with the development of cloud computing technology, the trend of large-scale deployment of important business applications in cloud centers has greatly increased. The development and use of software-defined networks in cloud data centers have greatly reduced the effect of traditional network security boundary protection. How to find an effective way to protect important applications in open multi-step large-scale cloud data centers is a problem we need to solve. Threat intelligence has become an important means to solve complex network attacks, realize real-time threat early warning and attack tracking because of its ability to analyze the threat intelligence data of various network attacks. Based on the research of threat intelligence, machine learning, cloud central network, SDN and other technologies, this paper proposes an active defense method of network security based on threat intelligence for super-large cloud data centers.","PeriodicalId":117159,"journal":{"name":"2021 6th International Conference on Intelligent Computing and Signal Processing (ICSP)","volume":"58 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-04-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130473335","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

2021 6th International Conference on Intelligent Computing and Signal Processing (ICSP) Pub Date : 2021-04-09 DOI: 10.1109/ICSP51882.2021.9408942

Zhanli Li, Pengfei Song

引用次数: 1

Scoop blood pressure analysis based on Blackman window 基于布莱克曼窗的血压分析

2021 6th International Conference on Intelligent Computing and Signal Processing (ICSP) Pub Date : 2021-04-09 DOI: 10.1109/ICSP51882.2021.9408990

Anqi Guan, N. Zhou, Yuhang Tang

引用次数: 0

Decomposition of EEG signal and detection of sleep spindle using sparse optimization 基于稀疏优化的脑电信号分解与睡眠纺锤波检测

2021 6th International Conference on Intelligent Computing and Signal Processing (ICSP) Pub Date : 2021-04-09 DOI: 10.1109/ICSP51882.2021.9409011

Chen-Xin Fang, Mei-Jing Sun, Zhen-Hua Zhao

引用次数: 0

Contact dynamics of frictional flexible telescopic manipulator 摩擦柔性伸缩机械臂的接触动力学

2021 6th International Conference on Intelligent Computing and Signal Processing (ICSP) Pub Date : 2021-04-09 DOI: 10.1109/ICSP51882.2021.9408708

J. Zhang, Mingyang Fang, Huadong Shao

引用次数: 0

Efficient DOA Estimation Method for Wideband Uncorrelated Signals 宽带不相关信号的有效DOA估计方法

2021 6th International Conference on Intelligent Computing and Signal Processing (ICSP) Pub Date : 2021-04-09 DOI: 10.1109/ICSP51882.2021.9408958

Jin Zhang, Hui Gao, Kui Zhang, Jiren Xu

引用次数: 0

Research on Friction Pressure Prediction of hydraulic fracturing Based on RBF Neural Network 基于RBF神经网络的水力压裂摩擦压力预测研究

2021 6th International Conference on Intelligent Computing and Signal Processing (ICSP) Pub Date : 2021-04-09 DOI: 10.1109/ICSP51882.2021.9408783

Fei Chen, Xiao-ming Chi, Zhi Jing

引用次数: 1

Traceability algorithm of meat pigeon quality and safety based on cooperative sensing tracking and recognition 基于协同传感跟踪识别的肉鸽质量安全追溯算法

2021 6th International Conference on Intelligent Computing and Signal Processing (ICSP) Pub Date : 2021-04-09 DOI: 10.1109/ICSP51882.2021.9408732

Peihao Liu, Kaijun Mai, Hao Zhang, Shilong Qiu

{"title":"Traceability algorithm of meat pigeon quality and safety based on cooperative sensing tracking and recognition","authors":"Peihao Liu, Kaijun Mai, Hao Zhang, Shilong Qiu","doi":"10.1109/ICSP51882.2021.9408732","DOIUrl":"https://doi.org/10.1109/ICSP51882.2021.9408732","url":null,"abstract":"In order to improve the ability of quality and safety management and process supervision for meat pigeons, a design method of quality and safety traceability system for meat pigeons based on collaborative sensing tracking and identification was proposed. Firstly, the cooperative sensing RFID tag identification model is used to collect information in the process of meat pigeon quality and safety traceability, and the cooperative sensing tracking and RFID tag identification technology and Internet of Things technology are used to control the data transmission and reception of meat pigeon quality and safety traceability. A multidimensional sensor parameter fusion model is designed to track and identify meat pigeon quality and safety, and the distribution characteristics of meat pigeon quality and safety are extracted. The fuzzy clustering method is used to classify the statistical information of quality and safety information of meat pigeons, and the combination of forward tracing and reverse tracing is used to realize the fusion of multi-dimensional sensor parameters of quality and safety tracing sources of meat pigeons, and realize the optimization design of quality and safety tracing algorithm of meat pigeons. The simulation results show that the information recognition ability of the quality and safety traceability of meat pigeons is better, and the real-time and accuracy of the quality and safety traceability of meat pigeons are improved.","PeriodicalId":117159,"journal":{"name":"2021 6th International Conference on Intelligent Computing and Signal Processing (ICSP)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-04-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121375010","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

Image Defect Detection and Segmentation Algorithm of Solar Cell Based on Convolutional Neural Network 基于卷积神经网络的太阳能电池图像缺陷检测与分割算法

2021 6th International Conference on Intelligent Computing and Signal Processing (ICSP) Pub Date : 2021-04-09 DOI: 10.1109/ICSP51882.2021.9408827

Song Tian, Weijun Li, Shuang Li, Guangyan Tian, Linjun Sun, X. Ning

{"title":"Image Defect Detection and Segmentation Algorithm of Solar Cell Based on Convolutional Neural Network","authors":"Song Tian, Weijun Li, Shuang Li, Guangyan Tian, Linjun Sun, X. Ning","doi":"10.1109/ICSP51882.2021.9408827","DOIUrl":"https://doi.org/10.1109/ICSP51882.2021.9408827","url":null,"abstract":"The use of infrared or electroluminescence(EL) images of solar cell modules for defect detection is a very important method in non-destructive testing. Traditionally, this work is done by skilled technicians, which is time-consuming and susceptible to subjective factors. The surface defect detection method of solar cells based on machine learning has become one of the main research directions because of its high efficiency and convenience. For this reason, this paper proposes an improved fusion model based on VGGNet and U-Net++, which is used for defect detection and segmentation of EL images of solar cells. In the defect detection stage, the input image is processed pertinently, and by modifying the convolutional layer and the fully connected layer of the network, while improving the performance of the algorithm, it accelerates the convergence and avoids the phenomenon of over-fitting. In the defect segmentation stage, the defect location is marked based on the public data set, which is used for the training of each segmentation model, and the effect of different segmentation networks is compared to select a reasonable model. The experimental results show that the defect detection accuracy of the improved VGG16 network on the elpv-dataset is 95.2%, and the U-Net++ defect segmentation model has an average MIoU value of 0.955, which is better than other existing methods.","PeriodicalId":117159,"journal":{"name":"2021 6th International Conference on Intelligent Computing and Signal Processing (ICSP)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-04-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121418052","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: 4