2021 IEEE International Conference on Artificial Intelligence and Industrial Design (AIID)最新文献_第6页

Lagrange based Kinematic Control for a Class of Mobile Manipulators with Physical Constraints 一类带物理约束的移动机械臂的拉格朗日运动控制

2021 IEEE International Conference on Artificial Intelligence and Industrial Design (AIID) Pub Date : 2021-05-28 DOI: 10.1109/AIID51893.2021.9456566

Xiaojing Lv, Enhua Xu, Juanxiu Liu

引用次数: 2

Research on Maintenance Method of Typical Aircraft Electronic Equipment Based on Thermal Analysis Technology 基于热分析技术的典型飞机电子设备维修方法研究

2021 IEEE International Conference on Artificial Intelligence and Industrial Design (AIID) Pub Date : 2021-05-28 DOI: 10.1109/AIID51893.2021.9456508

Yang Yong

引用次数: 0

Research on Intelligent Pet Management Platform System Based on Big Data Environment 基于大数据环境的智能宠物管理平台系统研究

2021 IEEE International Conference on Artificial Intelligence and Industrial Design (AIID) Pub Date : 2021-05-28 DOI: 10.1109/AIID51893.2021.9456589

Huajie Luo, Yuqiang Wen, Xiao-Feng Zhang

{"title":"Research on Intelligent Pet Management Platform System Based on Big Data Environment","authors":"Huajie Luo, Yuqiang Wen, Xiao-Feng Zhang","doi":"10.1109/AIID51893.2021.9456589","DOIUrl":"https://doi.org/10.1109/AIID51893.2021.9456589","url":null,"abstract":"This paper mainly focuses on the design and implementation of the pet community platform system based on big data. Pet community platform system is divided into two subsystems: client and administrator. The two subsystems are developed in the way of front and rear end separation. The back end uses the current mainstream JavaWeb development framework SpringBoot+ MyBatisPlus, and the front end uses the popular VUE +Element UI framework. The database of the system uses MySQL8 +Redis, and the platform system uses NGINX to achieve load balancing. After system requirements, feasibility analysis, business analysis, case analysis, system function of activity diagram and the database design and detailed design, using the MVC model view controller design specification, design to achieve the system each function module, through the way of writing test cases and manual test to test the main functions of the system, the system of the client subsystem mainly for the majority of raising pet pet professionals provide a communication platform with pet as the theme of community, published on the platform users can questions about pets or subject, the platform can communicate the case for users. This system use enterprise Java applications for pet lovers create pet exchange platform for the community, the community will gather all kinds of pet owners, users can learn all kinds of pets here knowledge and skills, to communicate with other pet owners to discuss, share moments of pet, pet adoption information release, we work together to solve the problem of pet relocation. At the same time, it provides data collection and analysis to provide strong data support for the development of pet market.","PeriodicalId":412698,"journal":{"name":"2021 IEEE International Conference on Artificial Intelligence and Industrial Design (AIID)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-05-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127517725","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

Confine Keypoint Triplets for Object Detection 限制关键点三元组用于对象检测

2021 IEEE International Conference on Artificial Intelligence and Industrial Design (AIID) Pub Date : 2021-05-28 DOI: 10.1109/AIID51893.2021.9456588

Guobin Xu, Sheng Tang, Zhengfa Yu, Kai Fu

{"title":"Confine Keypoint Triplets for Object Detection","authors":"Guobin Xu, Sheng Tang, Zhengfa Yu, Kai Fu","doi":"10.1109/AIID51893.2021.9456588","DOIUrl":"https://doi.org/10.1109/AIID51893.2021.9456588","url":null,"abstract":"Corner-based object detection algorithm is a hot topic in academia and industry. Scholars have applied it to different scenarios such as 3D object detection, object tracking, pose estimation and so on. The core of this method is to detect and match corner points. Although a considerable number of papers have been studied on this issue, there are still a lot of missed detection and false detection. In this paper, we pro-posed a one-stage object detection method with confine key- point triplets(ConfineNet), which applies center pooling and corner matching limit in local feature region. This restrictions can provide stronger correlation features with the object for subsequent prediction of center points, which can help to improve the prediction results of center points and corner matching. In addition, ConfineNet learns the association distance between the upper-left corner point and the lower-right corner point, which can confine the corner matching within a local area, thereby reducing matching errors. The AP value of Confine- Net reaches 48.2% on MS-COCO test-dev. our ConfineNet not only outperforms all existing anchor-free detectors but also achieves comparable performance to the state-of-the-art of two-stage detection approaches.","PeriodicalId":412698,"journal":{"name":"2021 IEEE International Conference on Artificial Intelligence and Industrial Design (AIID)","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-05-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121523000","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

Market Forecast using XGboost and Hyperparameters Optimized by TPE 利用XGboost和TPE优化的超参数进行市场预测

2021 IEEE International Conference on Artificial Intelligence and Industrial Design (AIID) Pub Date : 2021-05-28 DOI: 10.1109/AIID51893.2021.9456538

Yang Yang

引用次数: 2

Specific Emitter Identification based on Multi-Domain Features Learning 基于多域特征学习的特定发射器识别

2021 IEEE International Conference on Artificial Intelligence and Industrial Design (AIID) Pub Date : 2021-05-28 DOI: 10.1109/AIID51893.2021.9456526

Rundong Li, Jianhao Hu, Shaoqian Li, Weiwei Ai

{"title":"Specific Emitter Identification based on Multi-Domain Features Learning","authors":"Rundong Li, Jianhao Hu, Shaoqian Li, Weiwei Ai","doi":"10.1109/AIID51893.2021.9456526","DOIUrl":"https://doi.org/10.1109/AIID51893.2021.9456526","url":null,"abstract":"Specific emitter identification (SEI) is a technology to extract the subtle fingerprint features of the received electromagnetic signal, and identify the emitters to which the signal belongs. It has important applications in military and civil occasions. Traditionally, expert-experience is used for feature extraction, which is time-consuming and unstable. In order to overcome this shortcoming, this paper proposes an Intelligent Radiometric Identification algorithm base on Time and Frequency domain feature Fusion (IRI-TFF) which uses deep learning technology. The algorithm designs a new multi-domain fused one-dimensional complex-valued densely connected convolutional network (DenseNet) model after the accurate “calibration” preprocessing of the received signal and the combination of time and frequency domain data as training examples. Meanwhile, three fusion strategies are proposed. The experimental results show that the proposed algorithm is superior to the traditional expert-experience based SEI algorithm or other similar deep learning based SEI algorithm, and is robust to noises.","PeriodicalId":412698,"journal":{"name":"2021 IEEE International Conference on Artificial Intelligence and Industrial Design (AIID)","volume":"194 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-05-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131886142","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

The Development Status and Trend of Airborne Multifunctional Radar 机载多功能雷达的发展现状与趋势

2021 IEEE International Conference on Artificial Intelligence and Industrial Design (AIID) Pub Date : 2021-05-28 DOI: 10.1109/AIID51893.2021.9456504

Tianhao Gao, Qu Wei, Pengda Wang, Yaoyao Dong, Haohao Jiang, Bakun Zhu

引用次数: 1

Analysis of the research status of phase interferometer deblurring 相位干涉仪去模糊的研究现状分析

2021 IEEE International Conference on Artificial Intelligence and Industrial Design (AIID) Pub Date : 2021-05-28 DOI: 10.1109/AIID51893.2021.9456522

Feilong Mao, Hong Ma, Yiwen Jiao, Dong Li, Zefu Gao

引用次数: 0

Research on elevator speed governor calibration software based on image processing 基于图像处理的电梯调速器标定软件研究

2021 IEEE International Conference on Artificial Intelligence and Industrial Design (AIID) Pub Date : 2021-05-28 DOI: 10.1109/AIID51893.2021.9456495

Feng Shuangchang, Zhang Pengzhao, Shen Wenhao, Chen Jie

引用次数: 1

Fast-robust book information extraction system for automated intelligence library 自动化智能图书馆快速鲁棒图书信息提取系统

2021 IEEE International Conference on Artificial Intelligence and Industrial Design (AIID) Pub Date : 2021-05-28 DOI: 10.1109/AIID51893.2021.9456499

Yusen Xie, Ting Sun, Xinglong Cui, Shuixin Deng, Lei Deng, Baohua Chen

{"title":"Fast-robust book information extraction system for automated intelligence library","authors":"Yusen Xie, Ting Sun, Xinglong Cui, Shuixin Deng, Lei Deng, Baohua Chen","doi":"10.1109/AIID51893.2021.9456499","DOIUrl":"https://doi.org/10.1109/AIID51893.2021.9456499","url":null,"abstract":"At present, in the large-scale book management scene, book sorting, daily maintenance and book retrieval are very common, but the book information is complicated and the efficiency of relying on manual management is extremely poor. Although there have been many self-service book systems based on optics or vision, they are mostly based on traditional computer vision algorithms such as boundary extraction. Due to the fact that there are more artificial experience thresholds, some shortcomings such as low detection accuracy, poor robustness, and inability to systematically deploy on a large scale, which lack of insufficient intelligence. Therefore, we proposed a book information extraction algorithm based on object detection and optical character recognition (OCR) that is suitable for multiple book information recognition, multiple book image angles and multiple book postures. It can be applied to scenes such as book sorting, bookshelf management and book retrieval. The system we designed includes the classification of book covers and back covers, the classification of books upright and inverted, the detection of book pages side and spine side, the recognition of book pricing. In terms of accuracy, the classification accuracy of the front cover and the back cover is 99.9%, the upright classification accuracy of book front covers is 98.8%, the back cover reaches 99.9%, the accuracy of book price recognition get 94.5%, and the book spine/page side detection mAP reaches 99.6%; in terms of detection speed, Yolov5 detection model was improved and the statistical-based pre-pruning strategy was adopted, support by our algorithm the system reaches 2.09 FPS in book price recognition, which improves the detection speed to meet actual needs.","PeriodicalId":412698,"journal":{"name":"2021 IEEE International Conference on Artificial Intelligence and Industrial Design (AIID)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-05-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133294527","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