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2021 International Conference on Computer Engineering and Artificial Intelligence (ICCEAI)最新文献

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Using binocular vision to measure wave characteristic 利用双目视觉测量波特性
2021 International Conference on Computer Engineering and Artificial Intelligence (ICCEAI) Pub Date : 2021-08-01 DOI: 10.1109/ICCEAI52939.2021.00044
Lei Shi, Li Hui, Jing Shi, Bin Zhao, Xiao Cui, Shibo Chu
{"title":"Using binocular vision to measure wave characteristic","authors":"Lei Shi, Li Hui, Jing Shi, Bin Zhao, Xiao Cui, Shibo Chu","doi":"10.1109/ICCEAI52939.2021.00044","DOIUrl":"https://doi.org/10.1109/ICCEAI52939.2021.00044","url":null,"abstract":"The paper presented a new wave acquisition stereo system to estimate significant wave height based on stereo (binocular) vision. Using binocular vision, wave transformation in near shore water can be measured in wave altitude. The total measurement numbers are 1024 times. Wave vertical altitudes can be extracted from the datum according to binocular vision. With the help of 3D Fourier transform, the wave surface data can be turned into wave spectrum. By analyzing the wave spectrum, significant wave height can be estimated. Experimental results have shown that the method is effective.","PeriodicalId":331409,"journal":{"name":"2021 International Conference on Computer Engineering and Artificial Intelligence (ICCEAI)","volume":"20 4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115543115","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
Anomaly detection of electricity load data based on MixMatch 基于MixMatch的电力负荷数据异常检测
2021 International Conference on Computer Engineering and Artificial Intelligence (ICCEAI) Pub Date : 2021-08-01 DOI: 10.1109/ICCEAI52939.2021.00010
S. Sun, Yatong Zhou, Haonuo He, Jingfei He, Yue Chi
{"title":"Anomaly detection of electricity load data based on MixMatch","authors":"S. Sun, Yatong Zhou, Haonuo He, Jingfei He, Yue Chi","doi":"10.1109/ICCEAI52939.2021.00010","DOIUrl":"https://doi.org/10.1109/ICCEAI52939.2021.00010","url":null,"abstract":"With the development of power industry, electricity has become one of the most important energy sources in our country, related to the lifeline of the country's economy. The electricity system is becoming more and more mature, but abnormal electricity consumption behaviors are also emerging endlessly, causing potential safety hazards in the electricity industry and even the electricity supply system. Considering the lack of abnormal annotations in the electricity load data, this paper proposes a semi-supervised electricity load data anomaly detection method based on MixMatch. Firstly, data cleaning of electricity load data is used to remove incorrect data. Secondly, Convolutional Autoencoder (CAE) is used to extract its time-domain and frequency-domain features separately, and the features are combined through feature fusion. Thirdly, the Borderline Synthetic Minority Oversampling Technique (Borderline-SMOTE) is used to solve the problem of data imbalance. The MixMatch semi-supervised algorithm is used to label the abnormal data to realize the anomaly detection of the electricity load data. Finally, this paper uses the k-means clustering and T-Stochastic neighbour Embedding (T -SNE) to classify the abnormal data and visualize the data. The experimental results show that, compared with traditional machine learning methods, the proposed method has a significant improvement on AUC.","PeriodicalId":331409,"journal":{"name":"2021 International Conference on Computer Engineering and Artificial Intelligence (ICCEAI)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114672067","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
Research on 3D Visual Cooperative Maintenance Method for Bogie of Urban Rail Vehicle 城市轨道车辆转向架三维视觉协同维修方法研究
2021 International Conference on Computer Engineering and Artificial Intelligence (ICCEAI) Pub Date : 2021-08-01 DOI: 10.1109/ICCEAI52939.2021.00079
Yi Liu, Qi Chang, Qinghai Gan, Fengyun Xie
{"title":"Research on 3D Visual Cooperative Maintenance Method for Bogie of Urban Rail Vehicle","authors":"Yi Liu, Qi Chang, Qinghai Gan, Fengyun Xie","doi":"10.1109/ICCEAI52939.2021.00079","DOIUrl":"https://doi.org/10.1109/ICCEAI52939.2021.00079","url":null,"abstract":"As the growing of individual demand and the requirement of environmental protection, the species of modern rail traffic equipment are increasing. System integration and coupling complexity require the maintenance personnel's knowledge, which also increases the economic burden of the enterprise. This study proposes a new 3D visualization and collaborative maintenance method for the product maintenance of rail traffic equipment manufacturing enterprises, which enables maintenance staff and experts to complete the collaborative operation or guiding behavior by integrating the information models of maintenance process and maintenance schedules based on human-computer interaction, information visualization and sharing methods. This technical scheme will establish a good platform that avoids the disadvantage of the traditional maintenance process guidance way. This work can improve the efficiency of maintenance work and reduce the waste of resources in the maintenance process.","PeriodicalId":331409,"journal":{"name":"2021 International Conference on Computer Engineering and Artificial Intelligence (ICCEAI)","volume":"142 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127322800","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
Evaluating the Speedup of Multicore Architecture on the Topological Characteristics of On-chip Memory 基于片上存储器拓扑特性的多核结构加速评估
2021 International Conference on Computer Engineering and Artificial Intelligence (ICCEAI) Pub Date : 2021-08-01 DOI: 10.1109/ICCEAI52939.2021.00098
Hong Zhang, Xiaojun Wang
{"title":"Evaluating the Speedup of Multicore Architecture on the Topological Characteristics of On-chip Memory","authors":"Hong Zhang, Xiaojun Wang","doi":"10.1109/ICCEAI52939.2021.00098","DOIUrl":"https://doi.org/10.1109/ICCEAI52939.2021.00098","url":null,"abstract":"Being the most important underlying backbone of a multicore processor, the interconnection network for on-chip memory has a significant impact on the performance of a multicore processor. The evaluation for the type network is almost the first step of designing a new architecture for a multicore processor. For this type of evaluation, however, there are few effective methods available because of the too much uncertainty, especially the need to compare with a great number of different multicore networks on chip. This article presents ETOM (Evaluation on Topology of On-chip Memory), a new method to evaluate the speedup of multicore architectures. ETOM can accurately figure out the contribution of each core to the overall performance of a multicore processor, while all of the cores are controlled by the topology of on-chip memory network, the contributions of cores can certainly illustrate how and how much the topology affects the overall performance, and then a targeted modification to the topology can be made.","PeriodicalId":331409,"journal":{"name":"2021 International Conference on Computer Engineering and Artificial Intelligence (ICCEAI)","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127496230","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
Hyperspectral image fusion by hybrid regularizations with local low-rank 局部低秩混合正则化的高光谱图像融合
2021 International Conference on Computer Engineering and Artificial Intelligence (ICCEAI) Pub Date : 2021-08-01 DOI: 10.1109/ICCEAI52939.2021.00022
Zhaoyang Liu, Mingxi Ma, Zhaoming Wu
{"title":"Hyperspectral image fusion by hybrid regularizations with local low-rank","authors":"Zhaoyang Liu, Mingxi Ma, Zhaoming Wu","doi":"10.1109/ICCEAI52939.2021.00022","DOIUrl":"https://doi.org/10.1109/ICCEAI52939.2021.00022","url":null,"abstract":"Hyperspectral images usually have higher spectral resolution but lower spatial resolution, compared with the multispectral images. Low spatial resolution brings difficulties to the practical applications of hyperspectral images. Therefore, to get high spatial resolution hyperspectral image, it is very important to fuse low spatial resolution hyperspectral image with the high spatial resolution multispectral image in the same scene. In this paper, we propose a hybrid regularization model by integrating sparse prior, local low-rank regularization and total variation based on l2 norm to reconstruct high spatial resolution hyperspectral images. In addition, we design an alternating direction method of multipliers (ADMM) to solve it. The experimental results show the superiority and competitiveness of our method over the state-of-the-art methods.","PeriodicalId":331409,"journal":{"name":"2021 International Conference on Computer Engineering and Artificial Intelligence (ICCEAI)","volume":"133 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115682023","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 Deep Learning Based Optimal Combination of Multidimensional Features in Large-Scene Laser Point Clouds Classification 基于深度学习的大场景激光点云多维特征最优组合分类研究
2021 International Conference on Computer Engineering and Artificial Intelligence (ICCEAI) Pub Date : 2021-08-01 DOI: 10.1109/ICCEAI52939.2021.00033
Lei Wang, Zhiyong Zhang, Xiaonan Li
{"title":"Research on Deep Learning Based Optimal Combination of Multidimensional Features in Large-Scene Laser Point Clouds Classification","authors":"Lei Wang, Zhiyong Zhang, Xiaonan Li","doi":"10.1109/ICCEAI52939.2021.00033","DOIUrl":"https://doi.org/10.1109/ICCEAI52939.2021.00033","url":null,"abstract":"As the self-occlusion or occluded 3D point clouds objects in complex scenes, which could affect the accuracy of objects classification, we propose Optimal Combination of Multidimensional Features based on deep learning for large-scene laser point clouds in classification. We construct the optimal combination matrix of multidimensional features by extracting the three-dimensional features of the three-dimensional point cloud and the two-dimensional features in multiple directions. The multidimensional optimal combination features are introduced into the convolutional network. The experimental results show that effectiveness of classification for large-scale point clouds, the effectiveness of 3D feature of point cloud is higher than that of 2D feature. The classification accuracy of our method can reach 98.8% on the Large-Scene Point Cloud Oakland data set, which obtains the better classification accuracy than other classification algorithms the paper mentioned.","PeriodicalId":331409,"journal":{"name":"2021 International Conference on Computer Engineering and Artificial Intelligence (ICCEAI)","volume":"66 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128621306","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
A comparative study of deep learning approaches for Chinese Sentence Classification 中文句子分类的深度学习方法比较研究
2021 International Conference on Computer Engineering and Artificial Intelligence (ICCEAI) Pub Date : 2021-08-01 DOI: 10.1109/ICCEAI52939.2021.00045
Zhu Zeng
{"title":"A comparative study of deep learning approaches for Chinese Sentence Classification","authors":"Zhu Zeng","doi":"10.1109/ICCEAI52939.2021.00045","DOIUrl":"https://doi.org/10.1109/ICCEAI52939.2021.00045","url":null,"abstract":"One of the most commonly used natural language processing technologies is text classification. Spam detection, news text classification, information retrieval, emotion analysis, and intention judgment, among other applications, are all popular text classification applications [25]. Text classification is the process of assigning pre-defined class labels to text documents in order to shape semantic classes. Engineering, medical science, life science, social sciences and humanities, marketing, and government are only a few of the real-world applications. Machine learning and deep learning algorithms have recently become common and efficient methods for dealing with text classification problems involving labeled data [26]. The primary goal of text classification is to automatically assign texts to pre-defined categories based on their content. In this study, we will conduct a comparative study of the accuracies of different deep learning methods that include Bidirectional Encoder Representations from Transformers (BERT), Recurrent Neural Network (RNN), Convolutional Neural Network (CNN), and Region-based convolutional neural networks and compare the effectiveness of these deep-learning approaches in classifying Chinese news title text using the THUCNews dataset.","PeriodicalId":331409,"journal":{"name":"2021 International Conference on Computer Engineering and Artificial Intelligence (ICCEAI)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133320948","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
Stability Analysis and Application Research of Hybrid Dynamic System 混合动力系统稳定性分析及应用研究
2021 International Conference on Computer Engineering and Artificial Intelligence (ICCEAI) Pub Date : 2021-08-01 DOI: 10.1109/ICCEAI52939.2021.00082
Qianqian Wang, Minan Tang, Aimin An, Weili Liu, Kaiyue Zhang, Jiandong Qiu
{"title":"Stability Analysis and Application Research of Hybrid Dynamic System","authors":"Qianqian Wang, Minan Tang, Aimin An, Weili Liu, Kaiyue Zhang, Jiandong Qiu","doi":"10.1109/ICCEAI52939.2021.00082","DOIUrl":"https://doi.org/10.1109/ICCEAI52939.2021.00082","url":null,"abstract":"Aiming at the switching control model of hybrid system, the stability of hybrid system is discussed. Combined with the typical switching control model, the sufficient conditions for the hybrid switching system to remain stable when the switching discrete state is changed and the system energy is increased are given. By dividing the switched system into a more reasonable area and adjusting the control law in time, the optimal control of the switched system is achieved. The stability condition of traffic signal switching control is verified by simulation with the traffic signal switching model of key traffic nodes (regions) in unbalanced road network based on hybrid system model. The experimental results show that the hybrid switched control system has more outstanding advantages than the discrete dynamic and continuous dynamic systems in urban traffic signal control.","PeriodicalId":331409,"journal":{"name":"2021 International Conference on Computer Engineering and Artificial Intelligence (ICCEAI)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116983811","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
A New Bottom-up Human Pose Estimation Method by Body Center and Anchor Points 一种基于身体中心和锚点的自下而上人体姿态估计新方法
2021 International Conference on Computer Engineering and Artificial Intelligence (ICCEAI) Pub Date : 2021-08-01 DOI: 10.1109/ICCEAI52939.2021.00047
Jiahua Wu, H. Lee
{"title":"A New Bottom-up Human Pose Estimation Method by Body Center and Anchor Points","authors":"Jiahua Wu, H. Lee","doi":"10.1109/ICCEAI52939.2021.00047","DOIUrl":"https://doi.org/10.1109/ICCEAI52939.2021.00047","url":null,"abstract":"There are two stages in bottom-up human pose estimation method, joint detection and joint candidate grouping. Optimizing grouping algorithms can significantly improve the performance of pose estimation. In this paper, we introduce body center, a center point of person instance, and anchor point, a corresponding assistant position point, for the task of grouping. The anchor point is the center of joint and body center, which can help joint grouping to the corresponding person instance like an anchor. The body center and anchor point can be predicted simultaneously with the joint candidate by the same backbone. So, this new grouping method can fully exploit the features extracted by the step of joint detection. On the COCO keypoints dataset, the proposed method performs on par with the existing state-of-the-art bottom-up method in accuracy.","PeriodicalId":331409,"journal":{"name":"2021 International Conference on Computer Engineering and Artificial Intelligence (ICCEAI)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130344989","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
Lateral control design of intelligent chassis for fire robot 消防机器人智能底盘横向控制设计
2021 International Conference on Computer Engineering and Artificial Intelligence (ICCEAI) Pub Date : 2021-08-01 DOI: 10.1109/ICCEAI52939.2021.00069
B. Fan, Shiyou Zhang, Ye-hwa Chen, Yi Zhang, Zhangsheng Deng
{"title":"Lateral control design of intelligent chassis for fire robot","authors":"B. Fan, Shiyou Zhang, Ye-hwa Chen, Yi Zhang, Zhangsheng Deng","doi":"10.1109/ICCEAI52939.2021.00069","DOIUrl":"https://doi.org/10.1109/ICCEAI52939.2021.00069","url":null,"abstract":"This study aims to solve the problem of lateral motion control so that the fire robot accurately tracks the desired speed and desired path, so as to realize autonomous driving of the fire robot, reduce the casualties of firefighters in firefighting, and further improve the intelligence of firefighting. According to the use scenario of the fire robot, and comprehensive consideration of lightweight and energy saving, the mechanical structure of its chassis is designed, and the sliding mode variable structure and the radial basis function (RBF) neural network are combined to design the lateral motion controller on this basis. The control expression of the controller is derived. In order to verify the robustness of the controller, this study uses the ADAMS/Simulink co-simulation system, using different driving speeds to simulate and verify the controller under a typical route. The lateral controller studied in this paper plays an important role in the path tracking of fire robot.","PeriodicalId":331409,"journal":{"name":"2021 International Conference on Computer Engineering and Artificial Intelligence (ICCEAI)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130483442","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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