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

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Extraction Method of Judicial Language Entities Based On Regular Expression 基于正则表达式的司法语言实体抽取方法
2021 6th International Conference on Intelligent Computing and Signal Processing (ICSP) Pub Date : 2021-04-09 DOI: 10.1109/ICSP51882.2021.9408748
Jiao Kainan, Li Xin
{"title":"Extraction Method of Judicial Language Entities Based On Regular Expression","authors":"Jiao Kainan, Li Xin","doi":"10.1109/ICSP51882.2021.9408748","DOIUrl":"https://doi.org/10.1109/ICSP51882.2021.9408748","url":null,"abstract":"With the coming of the era of rule of law and intelligence, natural language processing technology plays a pivotal role. At present, a large number of unstructured judicial texts rely on manual processing and archiving. In order to make better use of them and achieve professional application, this paper proposes the goal of analyzing the structure of judgments, extracting the judicial language entities, and describing cases in the form of entity circulation map. As the text carrier of unstructured public events, the judicial document is of better standard format, finely crafted and easy processing, and becomes the research object of this paper. Through the survey of the development of named entity recognition technology, testing and contrasting the use of extraction tool, GATE, as well as considering the cost and effectiveness in the judicial field, this paper put forward a rule-based regular expression method for entity recognition. The scrapy crawler framework is used to obtain judgments classified from China Judgments Online website, so as to realize the task of analyzing the structure of judgments and extracting the judicial language entities.","PeriodicalId":117159,"journal":{"name":"2021 6th International Conference on Intelligent Computing and Signal Processing (ICSP)","volume":"206 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":"128611310","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
Blind Detection of Communication Signals Based on Improved YOLO3 基于改进YOLO3的通信信号盲检测
2021 6th International Conference on Intelligent Computing and Signal Processing (ICSP) Pub Date : 2021-04-09 DOI: 10.1109/ICSP51882.2021.9408998
Rundong Li, Jianhao Hu, Shaoqian Li, Shaohe Chen, Peng He
{"title":"Blind Detection of Communication Signals Based on Improved YOLO3","authors":"Rundong Li, Jianhao Hu, Shaoqian Li, Shaohe Chen, Peng He","doi":"10.1109/ICSP51882.2021.9408998","DOIUrl":"https://doi.org/10.1109/ICSP51882.2021.9408998","url":null,"abstract":"Blind detection of communication signals is a challenging task. In this paper, a general and novel blind detection method is proposed based on the similarity between communication signal detection and image object detection. We designed an improved YOLO3 model to detect the communication signals contained in the 2D wide-band spectrograms, the main innovates are as follows: 1) in order to reduce the burden of spectrograms labeling, an ingenious and automatic signal object labeling method is proposed; 2) in view of the fact that the communication signals are long and narrow objects in the spectrograms, the corresponding prior anchors are designed to improve the detection probability; 3) in order to improve the training efficiency and detection accuracy, the CIOU cost function and DIOU-NMS inference algorithm are introduced to achieve high-precision signal detection. The simulation results demonstrate that the proposed method can effectively detect the continuous and burst signals in wide-band communication signal data, and its performance is better than the traditional energy detection method.","PeriodicalId":117159,"journal":{"name":"2021 6th International Conference on Intelligent Computing and Signal Processing (ICSP)","volume":"8 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":"131934408","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
Research on Information Matrix of Highway Electromechanical System Based on Deep Convolutional Neural Networks 基于深度卷积神经网络的公路机电系统信息矩阵研究
2021 6th International Conference on Intelligent Computing and Signal Processing (ICSP) Pub Date : 2021-04-09 DOI: 10.1109/ICSP51882.2021.9408786
Weisu Zhang, Zichen Qian, Yazhong Guo, Chihang Zhao
{"title":"Research on Information Matrix of Highway Electromechanical System Based on Deep Convolutional Neural Networks","authors":"Weisu Zhang, Zichen Qian, Yazhong Guo, Chihang Zhao","doi":"10.1109/ICSP51882.2021.9408786","DOIUrl":"https://doi.org/10.1109/ICSP51882.2021.9408786","url":null,"abstract":"Health monitoring, intelligent management and the maintenance of highway electromechanical systems are the basis and prerequisite for the control of intelligent transportation equipment. Therefore, a method of constructing and classifying the condition information matrix of highway electromechanical system based on convolutional neural network is proposed. This method converts the electric power and electrical information collected by the electromechanical power distribution group of the Taizhou Bridge Highway into an information matrix method from time series, using convolutional neural network to classify and predict subsystem faults. The results show that the data processing method of the information matrix has an efficiency optimization effect on the identification of regional faults. At the same time, the construction based on the information matrix improves the scalability of the big data maintenance of the electromechanical system.","PeriodicalId":117159,"journal":{"name":"2021 6th International Conference on Intelligent Computing and Signal Processing (ICSP)","volume":"34 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":"134463385","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
Hand gesture recognition method based on dual-channel convolutional neural network 基于双通道卷积神经网络的手势识别方法
2021 6th International Conference on Intelligent Computing and Signal Processing (ICSP) Pub Date : 2021-04-09 DOI: 10.1109/ICSP51882.2021.9408844
Bingchao An, Wenpeng Zhang, xiangfeng Qiu, Yongxiang Liu
{"title":"Hand gesture recognition method based on dual-channel convolutional neural network","authors":"Bingchao An, Wenpeng Zhang, xiangfeng Qiu, Yongxiang Liu","doi":"10.1109/ICSP51882.2021.9408844","DOIUrl":"https://doi.org/10.1109/ICSP51882.2021.9408844","url":null,"abstract":"With the rapid development of security monitoring, assisted driving, remote health diagnosis and other fields in recent years, the recognition of human characteristics has attracted more and more attention. The wideband radar has a high range resolution compared to the narrow-band radar which make it able to extract fine features of human micro-movements. However, the micro-movement features of the human body are often in a complex background. Furthermore, the micro-movement features of the human body are weak compared to the main body. Therefore, the classification and recognition of human micro-motion based on wideband radar is still a difficult problem. Inspired by the successful application of convolutional neural network in image processing, this paper proposes a wideband hand gesture recognition method based on dual-channel convolutional neural network for wideband radar, which takes the range-Doppler map and high resolution range profile of human micro-motion as inputs. The effectiveness of this method is verified by experimental data, after the information is convolved, the features are fused, and finally the purpose of classification is achieved. The target recognition rate of this method is 95.67%, which is much higher than 89.87% of the High Resolution Range Profile(HRRP) and 88.61% of the Range Doppler(RD), which verifies the effectiveness of the method.","PeriodicalId":117159,"journal":{"name":"2021 6th International Conference on Intelligent Computing and Signal Processing (ICSP)","volume":"18 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":"133290232","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
Traffic Flow Prediction Model Based on LSTM with Finnish Dataset 基于芬兰数据集LSTM的交通流预测模型
2021 6th International Conference on Intelligent Computing and Signal Processing (ICSP) Pub Date : 2021-04-09 DOI: 10.1109/ICSP51882.2021.9408888
Qingling Chu, Guangze Li, Ruijie Zhou, Zhengdong Ping
{"title":"Traffic Flow Prediction Model Based on LSTM with Finnish Dataset","authors":"Qingling Chu, Guangze Li, Ruijie Zhou, Zhengdong Ping","doi":"10.1109/ICSP51882.2021.9408888","DOIUrl":"https://doi.org/10.1109/ICSP51882.2021.9408888","url":null,"abstract":"Accurate prediction of traffic flow can achieve reliable traffic control and inducement. To solve the problems of complex traditional prediction models and insufficient prediction accuracy, this paper proposes a traffic flow prediction model based on long short-term memory (LSTM). First, a real traffic flow dataset is selected to macroscopically analyze the traffic flow from the lane level. After that, the training set and test set are divided, and the LSTM is used to predict the traffic flow. The results of this algorithm are compared with those of gated recurrent unit (GRU) and stacked autoencoders (SAEs), and the results show that this algorithm has the lowest traffic flow fitting error and the highest performance.","PeriodicalId":117159,"journal":{"name":"2021 6th International Conference on Intelligent Computing and Signal Processing (ICSP)","volume":"2018 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":"131765443","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
Simulation of Satellite Attitude Control Based on BP Neural Network 基于BP神经网络的卫星姿态控制仿真
2021 6th International Conference on Intelligent Computing and Signal Processing (ICSP) Pub Date : 2021-04-09 DOI: 10.1109/ICSP51882.2021.9408751
Aidi Zhang, Yurong Liao, Shuyan Ni, Zhaoming Li, Xinyan Yang, DaShuang Yan
{"title":"Simulation of Satellite Attitude Control Based on BP Neural Network","authors":"Aidi Zhang, Yurong Liao, Shuyan Ni, Zhaoming Li, Xinyan Yang, DaShuang Yan","doi":"10.1109/ICSP51882.2021.9408751","DOIUrl":"https://doi.org/10.1109/ICSP51882.2021.9408751","url":null,"abstract":"In satellite attitude control algorithms, PID control is often used in engineering practice due to its simple, effective, stable and reliable characteristics. However, PID parameter tuning requires manual adjustment based on experience or a large number of experiments, which has a low efficiency. BP neural network is an intelligent algorithm based on the gradient descent method in the optimization theory, which can approximate any nonlinear function. This paper first establishes the satellite dynamic model under the ideal rigid body, then combines BP neural network with PID and applies it to satellite attitude control, where BP neural network's error back propagation characteristic is used to autonomously adjust the PID parameters, which improves the efficiency. The simulation shows that the step length has a great impact on the results of the control system, so it is necessary to select an appropriate step length for a specific task.","PeriodicalId":117159,"journal":{"name":"2021 6th International Conference on Intelligent Computing and Signal Processing (ICSP)","volume":"208 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":"132057578","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
Traffic Agent Movement Prediction Using ResNet-based Model 基于resnet模型的交通代理运动预测
2021 6th International Conference on Intelligent Computing and Signal Processing (ICSP) Pub Date : 2021-04-09 DOI: 10.1109/ICSP51882.2021.9408922
Kai-Qi Huang
{"title":"Traffic Agent Movement Prediction Using ResNet-based Model","authors":"Kai-Qi Huang","doi":"10.1109/ICSP51882.2021.9408922","DOIUrl":"https://doi.org/10.1109/ICSP51882.2021.9408922","url":null,"abstract":"Autonomous driving is a promising field, which brings conveniences to the life of people and optimizes the operations of the social system. Although many advantages it has, the complexity of autonomous driving hinders the applications of it in practice. autonomous driving is a comprehensive and complex project, which contains lots of difficult challenges. And the traffic agent movement prediction is one of them. In this paper, we regard the traffic agent movement prediction as a regression problem. And a deep neural network model of which the backbone is ResNet101 is proposed to deal with the regression. To demonstrate the efficiency of the proposed method, experiments on Lyft Motion Prediction for Autonomous Vehicles data set are conducted. And the quantitative comparisons of the experimental results indicate that the proposed method is more efficient on the traffic motion prediction than comparing methods.","PeriodicalId":117159,"journal":{"name":"2021 6th International Conference on Intelligent Computing and Signal Processing (ICSP)","volume":"41 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":"132181786","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
An Intelligent Life Jacket System Based on OneNET 基于OneNET的智能救生衣系统
2021 6th International Conference on Intelligent Computing and Signal Processing (ICSP) Pub Date : 2021-04-09 DOI: 10.1109/ICSP51882.2021.9408758
Kaixuan Wang, Kexuan Zhao, Mingyi Su, Jin Qi, Y. Hou, Sheng Tang
{"title":"An Intelligent Life Jacket System Based on OneNET","authors":"Kaixuan Wang, Kexuan Zhao, Mingyi Su, Jin Qi, Y. Hou, Sheng Tang","doi":"10.1109/ICSP51882.2021.9408758","DOIUrl":"https://doi.org/10.1109/ICSP51882.2021.9408758","url":null,"abstract":"In order to solve the problem of single function and low intelligence of traditional life jacket, an intelligent water life jacket system principle prototype is designed and developed. The system includes intelligent life jacket, OneNET Cloud Service Platform and mobile app. With MCU as the main control and water sensor as the falling water monitoring equipment, GPS real-time positioning information is uploaded to OneNET and mobile app through GPRS wireless, so as to realize the water safety monitoring and management of small and medium-sized waters. The simulation and field test show that the system can stably realize the functions of falling water detection, positioning, alarming and uploading. The working time of the whole process of the system is limited within 10 seconds, and the GPS precision is controlled within 10 meters. This project is expected to provide technical reference for the development of life-saving equipment and the safety management of small and medium waters, which has certain practical value.","PeriodicalId":117159,"journal":{"name":"2021 6th International Conference on Intelligent Computing and Signal Processing (ICSP)","volume":"38 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":"122384237","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
Selection of Communication Frequency Points for Shortwave Radio Network Based on VOACAP 基于VOACAP的短波无线网络通信频率点选择
2021 6th International Conference on Intelligent Computing and Signal Processing (ICSP) Pub Date : 2021-04-09 DOI: 10.1109/ICSP51882.2021.9408644
Yunhong Xie, Gang Min, HaiJun Bin, Hong Wang, Simin Ma
{"title":"Selection of Communication Frequency Points for Shortwave Radio Network Based on VOACAP","authors":"Yunhong Xie, Gang Min, HaiJun Bin, Hong Wang, Simin Ma","doi":"10.1109/ICSP51882.2021.9408644","DOIUrl":"https://doi.org/10.1109/ICSP51882.2021.9408644","url":null,"abstract":"In the past, it was difficult and unscientific to select the frequency of shortwave communication. Aiming at a specific problem, this paper proposes a frequency selection scheme for shortwave communication network, and calls the frequency selection software VOACAP to collect the input parameters such as the longitude and latitude of the receiving and transmitting ground, and calculates the output parameters such as the point-to-point frequency and antenna angle by using the sunspot data of the past few cycles. The calculation results are combined with the frequency selection scheme to select the final network frequency. In addition, the parameters such as the height of the antenna can guide the follow-up communication work. Communication organizations use this method to select the communication frequency of shortwave networking, which reduces the work intensity and greatly improves the communication passability.","PeriodicalId":117159,"journal":{"name":"2021 6th International Conference on Intelligent Computing and Signal Processing (ICSP)","volume":"2 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":"122857725","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
Emotion Recognition in Singing using Convolutional Neural Networks 基于卷积神经网络的歌唱情感识别
2021 6th International Conference on Intelligent Computing and Signal Processing (ICSP) Pub Date : 2021-04-09 DOI: 10.1109/ICSP51882.2021.9408959
Yingchao Shi, Xiao Zhou
{"title":"Emotion Recognition in Singing using Convolutional Neural Networks","authors":"Yingchao Shi, Xiao Zhou","doi":"10.1109/ICSP51882.2021.9408959","DOIUrl":"https://doi.org/10.1109/ICSP51882.2021.9408959","url":null,"abstract":"With the development of deep learning, convolution neural network (CNN) has been widely applied in the field of emotion recognition. The vital to enhance the performance of singing emotion recognition system is to select a suitable feature and establish reliable models. The feature of Mel Frequency Cepstral Coefficient (MFCC) method has been proved to be effective in recognizing emotions. Therefore, in this paper, CNN is used to build a model of singing emotion recognition system, and MFCC method is used in feature extraction. For improving the accuracy of this system, the feature matrices have been segmented into small slices, and the method of majority vote has been used in the test part to identify the emotion. To verify the generalization of this system, this paper provides two approaches in model building part. One approach distinguishes male and female speakers separately. The other one is to build a mixed model. The accuracy of the singing emotion recognition system has been improved in both approaches and is not influenced by using separate model or mixed model.","PeriodicalId":117159,"journal":{"name":"2021 6th International Conference on Intelligent Computing and Signal Processing (ICSP)","volume":"6 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":"123050722","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
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