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2020 IEEE International Conference on Industrial Application of Artificial Intelligence (IAAI)最新文献

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Adaptive Retrieval Method of Legal Information based on Artificial Intelligence 基于人工智能的法律信息自适应检索方法
2020 IEEE International Conference on Industrial Application of Artificial Intelligence (IAAI) Pub Date : 2020-12-25 DOI: 10.1109/IAAI51705.2020.9332812
G. Yang
{"title":"Adaptive Retrieval Method of Legal Information based on Artificial Intelligence","authors":"G. Yang","doi":"10.1109/IAAI51705.2020.9332812","DOIUrl":"https://doi.org/10.1109/IAAI51705.2020.9332812","url":null,"abstract":"In the current legal information retrieval methods, keywords are used for extraction and neural networks are used for search. However, the keywords of cases in legal information are different. Simply using keywords to extract the search results in insufficient accuracy. Therefore, an adaptive retrieval method of legal information based on artificial intelligence is proposed. First, establish a positional legal language model to determine the total number of spreads in the term. According to the definition of the term in the model, calculate the similarity of the semantic concept of the term. After confirming that the concept is similar to the term, calculate the co-occurring words in the term. Finally, an artificial intelligence algorithm is used to retrieve the co-occurring words. In order to verify the feasibility of the designed retrieval method, literature [1], literature [2] and design methods were used to retrieve the contents of a certain legal information database. The experimental results show that the designed retrieval method has a higher retrieval accuracy and meets the design requirements.","PeriodicalId":232194,"journal":{"name":"2020 IEEE International Conference on Industrial Application of Artificial Intelligence (IAAI)","volume":"50 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122814012","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
E-Commerce Human Capital Value Prediction Method based on Fuzzy Comprehensive Evaluation 基于模糊综合评价的电子商务人力资本价值预测方法
2020 IEEE International Conference on Industrial Application of Artificial Intelligence (IAAI) Pub Date : 2020-12-25 DOI: 10.1109/IAAI51705.2020.9332837
Yu-Min Wei
{"title":"E-Commerce Human Capital Value Prediction Method based on Fuzzy Comprehensive Evaluation","authors":"Yu-Min Wei","doi":"10.1109/IAAI51705.2020.9332837","DOIUrl":"https://doi.org/10.1109/IAAI51705.2020.9332837","url":null,"abstract":"The evaluation of human capital is a very complex task. How to confirm human capital in the corporate system, accurately measure the value of human capital, and consider the income rights of human capital has become a focus of academic research, and thus a design based on fuzzy Comprehensive evaluation method of e-commerce human capital value prediction. Through the first fuzzy comprehensive evaluation, the evaluation index system and evaluation standard set are established. Through the second fuzzy comprehensive evaluation, the human capital value prediction of e-commerce based on fuzzy comprehensive evaluation is completed. Experiments have proved that the e-commerce human capital value prediction method based on fuzzy comprehensive evaluation in this study is more accurate than traditional prediction methods, and the e-commerce human capital value prediction time is shorter, which has practical application significance.","PeriodicalId":232194,"journal":{"name":"2020 IEEE International Conference on Industrial Application of Artificial Intelligence (IAAI)","volume":"60 11","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120901871","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
Remote Monitoring System of Mechanical Manufacturing Equipment based on Digital Image Processing 基于数字图像处理的机械制造设备远程监控系统
2020 IEEE International Conference on Industrial Application of Artificial Intelligence (IAAI) Pub Date : 2020-12-25 DOI: 10.1109/iaai51705.2020.9332828
Wang Jun-ru
{"title":"Remote Monitoring System of Mechanical Manufacturing Equipment based on Digital Image Processing","authors":"Wang Jun-ru","doi":"10.1109/iaai51705.2020.9332828","DOIUrl":"https://doi.org/10.1109/iaai51705.2020.9332828","url":null,"abstract":"Precision instrument, machinery manufacturing equipment needs to use a monitoring system to monitor production details in real time during its production and processing. However, the traditional remote monitoring system has a weak ability to process monitoring images, resulting in a low peak signal-to-noise ratio of the system. The surveillance image is blurry. Therefore, based on digital image processing, a new remote monitoring system for machinery manufacturing equipment is designed. In hardware, the front-end of voltage signal acquisition is redesigned, and the communication circuit is optimized. In software, digital image processing technology is used to sharpen the image fuzzy contour, correct the image texture, and enhance the fuzzy details of the monitoring image; the remote positioning and monitoring function of the system is set to realize the remote monitoring of mechanical manufacturing equipment. Experimental results: Compared with the monitoring system under the traditional design, the peak signal-to-noise ratio of the remote monitoring system designed this time is much higher than that of the traditional monitoring system. Visible digital image processing technology can help the surveillance system to enhance the fuzzy details of the image.","PeriodicalId":232194,"journal":{"name":"2020 IEEE International Conference on Industrial Application of Artificial Intelligence (IAAI)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117180433","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 Face Recognition Technology Based on Deep Learning 基于深度学习的人脸识别技术研究
2020 IEEE International Conference on Industrial Application of Artificial Intelligence (IAAI) Pub Date : 2020-12-25 DOI: 10.1109/IAAI51705.2020.9332854
Zhou Chun-rong
{"title":"Research on Face Recognition Technology Based on Deep Learning","authors":"Zhou Chun-rong","doi":"10.1109/IAAI51705.2020.9332854","DOIUrl":"https://doi.org/10.1109/IAAI51705.2020.9332854","url":null,"abstract":"The traditional face recognition technology requires a lot of computation time for human face feature extraction, and the recognition accuracy is limited by the extracted face features. Aiming at the above problems, this paper studies face recognition technology based on deep learning. For the image to be recognized, the HOG feature is used to detect the face target in the image. In order to avoid the influence of facial expression and posture, face alignment processing is performed. After extracting the face recognition features in the image, the neural network is used to realize face recognition. Through comparison experiments with traditional face recognition technology, it is verified that the recognition technology using deep learning improves the recognition efficiency by about 1.5 times and has better recognition adaptability.","PeriodicalId":232194,"journal":{"name":"2020 IEEE International Conference on Industrial Application of Artificial Intelligence (IAAI)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121965196","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
Design of Intelligent Retrieval System for Visibility Animation Material Based on Data Mining 基于数据挖掘的可视性动画素材智能检索系统设计
2020 IEEE International Conference on Industrial Application of Artificial Intelligence (IAAI) Pub Date : 2020-12-25 DOI: 10.1109/IAAI51705.2020.9332872
Z. Liu
{"title":"Design of Intelligent Retrieval System for Visibility Animation Material Based on Data Mining","authors":"Z. Liu","doi":"10.1109/IAAI51705.2020.9332872","DOIUrl":"https://doi.org/10.1109/IAAI51705.2020.9332872","url":null,"abstract":"Due to the lack of information viscosity, the semantic consistency of the traditional visual animation material intelligent retrieval system is poor. A visual animation material intelligent retrieval system based on data mining is designed. In hardware design, SED1335 liquid crystal display and resistive touch screen are used to design AD7843 pin function to realize human-computer interaction; in software design, visual animation material data is clustered through data mining technology to obtain a class-centric material data set, Create an index for each data set, and use Lucene to realize intelligent retrieval. The test results show that: the designed visual animation material intelligent retrieval system based on data mining has strong correlation between the material data and the retrieval semantics are basically consistent, which is better than the traditional intelligent retrieval system.","PeriodicalId":232194,"journal":{"name":"2020 IEEE International Conference on Industrial Application of Artificial Intelligence (IAAI)","volume":"75 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122569947","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
Multi-Intelligent Vehicle Cooperative Formation Control Method based on Visual Navigation 基于视觉导航的多智能车辆协同编队控制方法
2020 IEEE International Conference on Industrial Application of Artificial Intelligence (IAAI) Pub Date : 2020-12-25 DOI: 10.1109/iaai51705.2020.9332843
Jianglin Lu
{"title":"Multi-Intelligent Vehicle Cooperative Formation Control Method based on Visual Navigation","authors":"Jianglin Lu","doi":"10.1109/iaai51705.2020.9332843","DOIUrl":"https://doi.org/10.1109/iaai51705.2020.9332843","url":null,"abstract":"There are many path information noises in the traditional multi-agent vehicle cooperative formation control method, which leads to poor dynamic stability. Use the image capture card in the visual navigation system to obtain the path information of multiple intelligent vehicles, enhance the image quality, extract the edge of the path, obtain the complete path feature, calculate the expected speed and expected position of the target intelligent car, and perform it on the original control protocol Improved to realize the cooperative formation control of multiple intelligent vehicles. The experimental results show that the designed multi-agent vehicle cooperative formation control method based on visual navigation has a timely and effective response to direction and acceleration, and the speed consistency is maintained at a high level, which shows that the dynamic steady-state performance of the control method has been improved.","PeriodicalId":232194,"journal":{"name":"2020 IEEE International Conference on Industrial Application of Artificial Intelligence (IAAI)","volume":"59 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131438645","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
Intelligent Recognition Method of Human Motion Global Features Based on Kinect Skeleton Information 基于Kinect骨骼信息的人体运动全局特征智能识别方法
2020 IEEE International Conference on Industrial Application of Artificial Intelligence (IAAI) Pub Date : 2020-12-25 DOI: 10.1109/IAAI51705.2020.9332893
Lei Tao
{"title":"Intelligent Recognition Method of Human Motion Global Features Based on Kinect Skeleton Information","authors":"Lei Tao","doi":"10.1109/IAAI51705.2020.9332893","DOIUrl":"https://doi.org/10.1109/IAAI51705.2020.9332893","url":null,"abstract":"In order to solve the problems of low recognition accuracy and poor real-time performance in the existing training and recognition of human movement posture under complex background, an intelligent recognition method of human motion global features based on Kinect skeleton information is designed. The data of skeletal pose feature points is obtained from Kinect, and the pose feature vector is calculated. The current real-time pose feature vector is matched with the preset standard pose feature vector. The matching degree of the two postures is fed back in real time to achieve the purpose of pose recognition. The experimental results show that the method can effectively match and recognize human action posture, with high recognition accuracy and strong real-time performance Scalability.","PeriodicalId":232194,"journal":{"name":"2020 IEEE International Conference on Industrial Application of Artificial Intelligence (IAAI)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131806419","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
Design of Shooting Attitude Control System for Soccer Robot based on Vision Tracking Technology 基于视觉跟踪技术的足球机器人射击姿态控制系统设计
2020 IEEE International Conference on Industrial Application of Artificial Intelligence (IAAI) Pub Date : 2020-12-25 DOI: 10.1109/IAAI51705.2020.9332850
Ren Jia
{"title":"Design of Shooting Attitude Control System for Soccer Robot based on Vision Tracking Technology","authors":"Ren Jia","doi":"10.1109/IAAI51705.2020.9332850","DOIUrl":"https://doi.org/10.1109/IAAI51705.2020.9332850","url":null,"abstract":"In the actual work of traditional robot shooting attitude control system, there are conversion errors in attitude conversion angle, which results in excessive redundant interference data, which leads to the small load capacity of the control system. Aiming at this problem, a soccer robot shooting attitude control system based on visual tracking technology is designed. In the hardware part, attitude angle sensor is selected and connected with hardware interface circuit. In the software part, visual tracking technology is used to track the soccer movement posture, and the equation of football shooting attitude transformation is set. The control parameters are introduced to control the attitude conversion angle error, and the system design is completed. The experimental instruments are prepared and the experimental environment is set up. Two traditional control systems are compared with the control system designed in this paper. The results show that the load capacity of the control system designed in this paper is the strongest.","PeriodicalId":232194,"journal":{"name":"2020 IEEE International Conference on Industrial Application of Artificial Intelligence (IAAI)","volume":"56 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132516609","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 two-stage Feature Mining Fusion Method based on Genetic Algorithm 基于遗传算法的两阶段特征挖掘融合方法研究
2020 IEEE International Conference on Industrial Application of Artificial Intelligence (IAAI) Pub Date : 2020-12-25 DOI: 10.1109/IAAI51705.2020.9332844
Li Ying, Zhaohui Xi
{"title":"Research on two-stage Feature Mining Fusion Method based on Genetic Algorithm","authors":"Li Ying, Zhaohui Xi","doi":"10.1109/IAAI51705.2020.9332844","DOIUrl":"https://doi.org/10.1109/IAAI51705.2020.9332844","url":null,"abstract":"In the actual fusion of two-stage feature data, reconstruction errors are easy to occur in the process of feature region reconstruction in different stages, resulting in too few final fusible mining indicators. To solve this problem, this paper designs a two-stage feature mining fusion method based on genetic algorithm. Based on the two-stage mining features, the two-stage feature areas are divided, and the feature area reconstruction project is controlled by setting the background template of the feature area. Then the genetic algorithm is used to construct the mining fusion mapping relationship, and different fusion levels are set to complete the research on the feature mining fusion method. Set up a two-stage feature experiment platform, mine feature data, take the feature data obtained as the experimental object, and use two traditional fusion methods to conduct comparative experiments with this article. The results show that the method in this paper can integrate the most index values, which proves that the method is more effective.","PeriodicalId":232194,"journal":{"name":"2020 IEEE International Conference on Industrial Application of Artificial Intelligence (IAAI)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133449103","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
Graphical Symbol Design System of Plane Advertisement Based on Visual Communication 基于视觉传达的平面广告图形符号设计系统
2020 IEEE International Conference on Industrial Application of Artificial Intelligence (IAAI) Pub Date : 2020-12-25 DOI: 10.1109/iaai51705.2020.9332892
Yue Jin, Z. Liu
{"title":"Graphical Symbol Design System of Plane Advertisement Based on Visual Communication","authors":"Yue Jin, Z. Liu","doi":"10.1109/iaai51705.2020.9332892","DOIUrl":"https://doi.org/10.1109/iaai51705.2020.9332892","url":null,"abstract":"The traditional graphic symbol design system of graphic advertisements contains few basic design elements. When designing graphic advertisements, the design tasks carried by the system are too large, resulting in too long response time of the design system. In response to this shortcoming, a visual communication-based Graphical symbol design system for graphic advertising. The hardware part chooses to design the core hardware of the system. According to the working requirements of the chip, the hardware connection circuit is designed, the graphic symbol form is converted, and the conversion parameters are calibrated. According to the requirements of visual communication, the graphic symbol database of graphic advertisement is constructed to complete the design of the design system. Set the experimental instrument parameters, set up the system test environment, and use two traditional design systems and the researched design system for experiments. The results show that the researched design system has the shortest response time.","PeriodicalId":232194,"journal":{"name":"2020 IEEE International Conference on Industrial Application of Artificial Intelligence (IAAI)","volume":"48 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134125892","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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