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

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Large-scale scene mapping and localization based on multi-sensor fusion 基于多传感器融合的大尺度场景映射与定位
2021 6th International Conference on Intelligent Computing and Signal Processing (ICSP) Pub Date : 2021-04-09 DOI: 10.1109/ICSP51882.2021.9408987
Liang Yu, L. Jie, Luo Haoru, Li Sijia
{"title":"Large-scale scene mapping and localization based on multi-sensor fusion","authors":"Liang Yu, L. Jie, Luo Haoru, Li Sijia","doi":"10.1109/ICSP51882.2021.9408987","DOIUrl":"https://doi.org/10.1109/ICSP51882.2021.9408987","url":null,"abstract":"In the absence of GPS signals, Simultaneous Localization and Mapping (SLAM) technology enables unmanned systems to accomplish map construction and autonomous navigation in unknown environments. At present, there are mainly methods for SLAM based on sensors such as lidar, camera, ultrasonic, Inertial Measurement Unit (IMU) and odometer for location environment. However, there are certain limitations in using a single sensor for SLAM in unknown environment. In order to solve the above problems, this paper summarizes the key problems faced by mainstream SLAM at present, and proposes a SLAM method based on multi-sensor fusion, which can make full use of the advantages of various sensors from the hardware structure and make up for the shortcomings of using a single sensor. Finally, the proposed method was verified on the platform of “JAC Electric Vehicle”, and the experimental results show that the proposed method can effectively avoid the influence caused by signal weakening, improve the positioning accuracy, and the system has stronger robustness and better tracking performance.","PeriodicalId":117159,"journal":{"name":"2021 6th International Conference on Intelligent Computing and Signal Processing (ICSP)","volume":"3 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":"122446024","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
Context-based Image Caption using Deep Learning 使用深度学习的基于上下文的图像标题
2021 6th International Conference on Intelligent Computing and Signal Processing (ICSP) Pub Date : 2021-04-09 DOI: 10.1109/ICSP51882.2021.9408871
Sizhen Li, Linlin Huang
{"title":"Context-based Image Caption using Deep Learning","authors":"Sizhen Li, Linlin Huang","doi":"10.1109/ICSP51882.2021.9408871","DOIUrl":"https://doi.org/10.1109/ICSP51882.2021.9408871","url":null,"abstract":"Image captioning is an important but difficult task. The existing image caption mainly adopts the encoding and decoding structure, the encoder mainly uses CNN as image feature extractors, and the decoder uses LSTM. The attention mechanism is also widely used in the current encoding and decoding structure. However, the existing image caption models based on the convolutional neural networks and recurrent neural networks have low accuracy in extracting useful information from images and have problems such as gradient explosion. To solve these problems, this paper proposes a context-based image caption generation model. The method applies Resnet and context-coding for feature extraction SCST, then SCST and LSTM is used for captioning The experimental results demonstrates the effectiveness of the proposed approach.","PeriodicalId":117159,"journal":{"name":"2021 6th International Conference on Intelligent Computing and Signal Processing (ICSP)","volume":"189 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":"131373008","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
Research on the Choice of Marching Route Based on Decision Tree Method 基于决策树方法的行军路线选择研究
2021 6th International Conference on Intelligent Computing and Signal Processing (ICSP) Pub Date : 2021-04-09 DOI: 10.1109/ICSP51882.2021.9408739
Zhu Tongxin, Shen Nan
{"title":"Research on the Choice of Marching Route Based on Decision Tree Method","authors":"Zhu Tongxin, Shen Nan","doi":"10.1109/ICSP51882.2021.9408739","DOIUrl":"https://doi.org/10.1109/ICSP51882.2021.9408739","url":null,"abstract":"This thesis transforms the choice of marching route into risky two-level decision-making by analyzing feasible alternative routes, road conditions and their occurrence probability. Based on the decision tree method, the thesis depicts a two-level decision tree of marching route. After calculating the expected marching time along each alternative route, the thesis identifies two-level optimal marching route based on the minimal expected loss criterion. The result of example analysis proves that the method is effective, and describes the process of multi-level decision-making of marching route in a clearer way.","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":"127004580","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
Multiobjective and Multistakeholder Recommender Systems 多目标和多利益相关者推荐系统
2021 6th International Conference on Intelligent Computing and Signal Processing (ICSP) Pub Date : 2021-04-09 DOI: 10.1109/ICSP51882.2021.9408940
Dandan Wang, Yan Chen
{"title":"Multiobjective and Multistakeholder Recommender Systems","authors":"Dandan Wang, Yan Chen","doi":"10.1109/ICSP51882.2021.9408940","DOIUrl":"https://doi.org/10.1109/ICSP51882.2021.9408940","url":null,"abstract":"As an effective information extraction tool, recommender systems(RSs) can effectively provide users with content strategies from a large amount of data. The traditional RS can discover the unknown products of users and satisfy their tastes. However, the preferences of other RS participants should also be considered, such as the platforms. The platform’s objective is different from that of users, and they want to maximize profits. In this paper, we adopt a multiobjective model MSMO for multistakeholders, in which customer relevance and profit of the platform are taken into consideration. By applying four evolution techniques, we are able to find Pareto front as optimal solutions. The solutions can keep the balance among multiple stakeholders. Experiments on a real-world data set reveal that our proposed model can significantly promote profit with little sacrifice in individual preference.","PeriodicalId":117159,"journal":{"name":"2021 6th International Conference on Intelligent Computing and Signal Processing (ICSP)","volume":"59 5","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-04-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134480073","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
Pixel-Level crack detection using an attention mechanism 使用注意机制的像素级裂纹检测
2021 6th International Conference on Intelligent Computing and Signal Processing (ICSP) Pub Date : 2021-04-09 DOI: 10.1109/ICSP51882.2021.9408784
Rui Li, Kefei Xu, Decheng Wu, Zhiqin Zhu
{"title":"Pixel-Level crack detection using an attention mechanism","authors":"Rui Li, Kefei Xu, Decheng Wu, Zhiqin Zhu","doi":"10.1109/ICSP51882.2021.9408784","DOIUrl":"https://doi.org/10.1109/ICSP51882.2021.9408784","url":null,"abstract":"This paper proposes a pixel-by-pixel automatic crack detection method ECCrack. The method based on the combination of a channel attention mechanism and fully convolutional neural network. The codec structure is combined with the channel attention mechanism to enhance network’s ability to utilize crack feature information. In the experiment, we verified this method on the road crack data set, and the F1-score reached 92.83, which is better than other methods. Besides, we also conducted ablation experiments on this method to prove the effectiveness of the increased mechanism.","PeriodicalId":117159,"journal":{"name":"2021 6th International Conference on Intelligent Computing and Signal Processing (ICSP)","volume":"13 1 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":"134106647","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
Analysis of COVID-19 Rebound Based on Natural Language Processing 基于自然语言处理的COVID-19反弹分析
2021 6th International Conference on Intelligent Computing and Signal Processing (ICSP) Pub Date : 2021-04-09 DOI: 10.1109/ICSP51882.2021.9408930
R. Tang, Lei Zhang, Guangbin Zhang, Jiaqi Wang
{"title":"Analysis of COVID-19 Rebound Based on Natural Language Processing","authors":"R. Tang, Lei Zhang, Guangbin Zhang, Jiaqi Wang","doi":"10.1109/ICSP51882.2021.9408930","DOIUrl":"https://doi.org/10.1109/ICSP51882.2021.9408930","url":null,"abstract":"The novel coronavirus epidemic hasn't finished in the world. The number of people who come down with this disease keeps increasing. Besides, people make some comments on the website, which may be related to the epidemic situation. This work will analyze this relationship and make some suggestions to governments. First, the crawler is used to get the data of public emotion. NLP is the main method in this work, which can classify the words we get based on an emotion dictionary. In the end, we do some further analysis and give the warning line of confirmed cases by regression, whose value is around 30 people.","PeriodicalId":117159,"journal":{"name":"2021 6th International Conference on Intelligent Computing and Signal Processing (ICSP)","volume":"62 5","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-04-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114042078","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
Detection of Flying Birds in Airport Monitoring Based on Improved YOLOv5 基于改进YOLOv5的机场监测中飞禽的检测
2021 6th International Conference on Intelligent Computing and Signal Processing (ICSP) Pub Date : 2021-04-09 DOI: 10.1109/ICSP51882.2021.9408797
Xiaohan Shi, Jun Hu, Xueyue Lei, Shiyou Xu
{"title":"Detection of Flying Birds in Airport Monitoring Based on Improved YOLOv5","authors":"Xiaohan Shi, Jun Hu, Xueyue Lei, Shiyou Xu","doi":"10.1109/ICSP51882.2021.9408797","DOIUrl":"https://doi.org/10.1109/ICSP51882.2021.9408797","url":null,"abstract":"Flying birds affect the safety of aircraft, and it’s difficult to effectively detect and discriminate bird targets because of their small sizes in large-field monitoring. To solve the problem of insufficient feature information of tiny targets and improve the detection performance, in this paper we introduce a method of channel attention mechanisms into the YOLOv5. By modeling the interdependence between channels, the proposed method adaptively learns the weights, to calibrate the feature responses between channels, guides the model to pay more attention to the features with abundant information, and finally improves the accuracy of tiny target detection. We also setup a measured dataset of tiny birds by taking images with optical equipment deployed in airports. The experimental results show that the improved model achieves a certain improvement in detection accuracy and recall rate compared with the original YOLOv5 algorithm.","PeriodicalId":117159,"journal":{"name":"2021 6th International Conference on Intelligent Computing and Signal Processing (ICSP)","volume":"42 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":"114057210","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: 16
5 G Research on Path Optimization System of Radio Resource Management and Distribution in the Context 5g环境下无线电资源管理与分配路径优化系统研究
2021 6th International Conference on Intelligent Computing and Signal Processing (ICSP) Pub Date : 2021-04-09 DOI: 10.1109/ICSP51882.2021.9408714
Xuan Zhou, Xuefeng Wei
{"title":"5 G Research on Path Optimization System of Radio Resource Management and Distribution in the Context","authors":"Xuan Zhou, Xuefeng Wei","doi":"10.1109/ICSP51882.2021.9408714","DOIUrl":"https://doi.org/10.1109/ICSP51882.2021.9408714","url":null,"abstract":"In recent years, with the rapid growth of wireless communication services and the increasing requirements for the transmission rate and quality of wireless comunication information, the available spectrum resources have become increasingly scarce. Therefore, how to make full use of spectrum resources has become a key issue in the development of wireless communication technology. As a key technology that can effectively improve spectrum utilization, cognitive radio has become a new hotspot in wireless communication research. In order to solve the problem that most cognitive radio scenarios have multiple primary users with strong activity in real life, a multi power cognitive access strategy based on the activity of multiple primary users is proposed. The mathematical expression of cognitive system throughput under the strategy is derived theoretically, and the computer simulation is carried out. The results show that the proposed cognitive access mechanism enables cognitive users to choose the optimal authorized channel for transmission, and adaptively adopts multi power access strategy, which not only reduces the interference to authorized users, but also maximizes the capacity of cognitive system.","PeriodicalId":117159,"journal":{"name":"2021 6th International Conference on Intelligent Computing and Signal Processing (ICSP)","volume":"30 2","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-04-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114133100","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
Distribution network fault diagnosis technology based on intelligent algorithm 基于智能算法的配电网故障诊断技术
2021 6th International Conference on Intelligent Computing and Signal Processing (ICSP) Pub Date : 2021-04-09 DOI: 10.1109/ICSP51882.2021.9408961
Kongxian Wang, Ying Shao, Liming Wang, K. Lei
{"title":"Distribution network fault diagnosis technology based on intelligent algorithm","authors":"Kongxian Wang, Ying Shao, Liming Wang, K. Lei","doi":"10.1109/ICSP51882.2021.9408961","DOIUrl":"https://doi.org/10.1109/ICSP51882.2021.9408961","url":null,"abstract":"Fast and accurate fault diagnosis of distribution network is the key to ensure the reliability and security of power supply in distribution network. For distribution network fault diagnosis technology at home and abroad at present, mainly around the fault section location and precise ranging from two aspects, this paper combined with the latest research results of distribution network fault diagnosis technology, summarizes the related technologies of section positioning and fault location method, including matrix algorithm, genetic algorithm (GA), neural network algorithm (NNA), particle swarm optimization (PSO) algorithm, traveling wave method, impedance method, fault wave record device intelligent algorithm, etc., analyzes the basic principle and advantages and disadvantages of each algorithm, finally, the future development of the fault diagnosis technology is prospected.","PeriodicalId":117159,"journal":{"name":"2021 6th International Conference on Intelligent Computing and Signal Processing (ICSP)","volume":"128 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":"114491484","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
Noise recognition and removal method based on intermediate parameters of image processing 基于图像处理中间参数的噪声识别与去除方法
2021 6th International Conference on Intelligent Computing and Signal Processing (ICSP) Pub Date : 2021-04-09 DOI: 10.1109/ICSP51882.2021.9408960
Wen-guang Ye, Yunyong Cheng, Yiran Tian, Tianmiao Lin, Sheng Lin
{"title":"Noise recognition and removal method based on intermediate parameters of image processing","authors":"Wen-guang Ye, Yunyong Cheng, Yiran Tian, Tianmiao Lin, Sheng Lin","doi":"10.1109/ICSP51882.2021.9408960","DOIUrl":"https://doi.org/10.1109/ICSP51882.2021.9408960","url":null,"abstract":"The data obtained during the measurement of optical 3D topography will directly affect the final measurement result. It is aimed at the noise and invalid measurement points that are difficult to identify and remove due to the hardware assembly error of the measurement system and the specular reflection during the structured light measurement. This article proposes a noise recognition and removal method based on the intermediate parameters of image processing. This method can make the measurement of point cloud data more accurate and reliable, and also avoid the more complicated and time-consuming point cloud data processing process. At the end of this article, experiments on noise identification and removal of large-scale point cloud data obtained by line laser scanning of engine blades were carried out. Experiments prove that this method can remove noise and invalid points in the point cloud under the premise of ensuring a certain accuracy, especially the measurement accuracy of the leaf edge.","PeriodicalId":117159,"journal":{"name":"2021 6th International Conference on Intelligent Computing and Signal Processing (ICSP)","volume":"2016 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":"114573602","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
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