2021 IEEE International Conference on Artificial Intelligence and Industrial Design (AIID)最新文献_第5页

Research on Wind Power Prediction Based on Time Series 基于时间序列的风电功率预测研究

2021 IEEE International Conference on Artificial Intelligence and Industrial Design (AIID) Pub Date : 2021-05-28 DOI: 10.1109/AIID51893.2021.9456531

Yumeng Zhang, Yuying Zhao

引用次数: 3

Research on Image Encryption Technology Based on Hyperchaotic System and DNA Encoding 基于超混沌系统和DNA编码的图像加密技术研究

2021 IEEE International Conference on Artificial Intelligence and Industrial Design (AIID) Pub Date : 2021-05-28 DOI: 10.1109/AIID51893.2021.9456457

Mengmeng Zhang, Wangchun Wu

引用次数: 5

Research on University Product System under Computer Science Aided Operation 计算机辅助操作下的高校产品系统研究

2021 IEEE International Conference on Artificial Intelligence and Industrial Design (AIID) Pub Date : 2021-05-28 DOI: 10.1109/AIID51893.2021.9456481

Ying Yu, Yue Sun

引用次数: 0

Research on face recognition algorithm based on multi task deep learning 基于多任务深度学习的人脸识别算法研究

2021 IEEE International Conference on Artificial Intelligence and Industrial Design (AIID) Pub Date : 2021-05-28 DOI: 10.1109/AIID51893.2021.9456559

Hainie Meng, Yunli Cheng

{"title":"Research on face recognition algorithm based on multi task deep learning","authors":"Hainie Meng, Yunli Cheng","doi":"10.1109/AIID51893.2021.9456559","DOIUrl":"https://doi.org/10.1109/AIID51893.2021.9456559","url":null,"abstract":"With the vigorous development of the new generation of information technology, deep learning technology based on big data has gradually become one of the mainstream technologies in the field of artificial intelligence. Face recognition is an important topic in the field of artificial intelligence and biometrics.It is widely used in business, security, identity authentication and many other aspects, and has become a dynamic research field.With the continuous improvement of application requirements, face recognition technology is no longer only for face identification, face attribute recognition is becoming more and more important.Firstly, a simplified multi task face recognition model is proposed and designed to speed up the operation;Secondly, the correlation among multiple learning tasks is used to improve the recognition accuracy of the model;After model training and selection, an end-to-end multi task face recognition model is obtained.The multi task face recognition algorithm can be fast and accurate in a short time, which can be widely used in intelligent driving behavior analysis, intelligent navigation and other fields.","PeriodicalId":412698,"journal":{"name":"2021 IEEE International Conference on Artificial Intelligence and Industrial Design (AIID)","volume":"9 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":"126969852","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

An Improved MSCNN Method for Underwater Image Defogging 一种改进的MSCNN水下图像去雾方法

2021 IEEE International Conference on Artificial Intelligence and Industrial Design (AIID) Pub Date : 2021-05-28 DOI: 10.1109/AIID51893.2021.9456545

Haoyue Wang, Xiangning Chen, Bijie Xu, S. Du, Yinan Li

{"title":"An Improved MSCNN Method for Underwater Image Defogging","authors":"Haoyue Wang, Xiangning Chen, Bijie Xu, S. Du, Yinan Li","doi":"10.1109/AIID51893.2021.9456545","DOIUrl":"https://doi.org/10.1109/AIID51893.2021.9456545","url":null,"abstract":"Underwater imagery is an important carrier and presentation of underwater information, which plays a vital role in the exploration, exploitation and utilization of marine resources. However, due to the limitations of objective imaging environment and equipment, the quality of underwater images is always poor, with degradation phenomena such as low contrast, blurred details and colour deviation, which seriously restrict the development of related fields. Therefore, how to enhance and recover degraded underwater images through post-production algorithms has received increasing attention from scholars. In recent years, with the rapid development of deep learning technology, great progress has been made in underwater image enhancement and restoration based on deep learning. In this paper, we propose an improved MSCNN underwater image defogging method, which combines Retinex and CLAHE for brightness equalization and contrast enhancement of underwater images, making the method more advantageous for complex situations such as low illumination, uneven illumination and obvious Rayleigh scattering phenomena in underwater environments, and conduct objective analysis and comparison of the recovered images to prove the effectiveness of this algorithm in underwater defogging and colour correction. The effectiveness of the algorithm for underwater defogging and colour correction is demonstrated by objective analysis and comparison of the recovered images.","PeriodicalId":412698,"journal":{"name":"2021 IEEE International Conference on Artificial Intelligence and Industrial Design (AIID)","volume":"72 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":"131278216","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 Logistics Transportation of Detection and Segmentation Based on Deep Learning 基于深度学习的物流运输检测与分割研究

2021 IEEE International Conference on Artificial Intelligence and Industrial Design (AIID) Pub Date : 2021-05-28 DOI: 10.1109/AIID51893.2021.9456490

Dun Liu, Zaichong Zheng

{"title":"Research on Logistics Transportation of Detection and Segmentation Based on Deep Learning","authors":"Dun Liu, Zaichong Zheng","doi":"10.1109/AIID51893.2021.9456490","DOIUrl":"https://doi.org/10.1109/AIID51893.2021.9456490","url":null,"abstract":"Nowadays, logistics transportation plays an increasingly important role in our life, and higher transportation efficiency has always been the goal of people. People can perform more efficient vehicle scheduling according to the quantity of goods. Therefore, obtaining the quantity of goods that needs to be transported is the key to improve the efficiency of logistics transportation. At present, the amount of goods can be counted by monitoring the change of objects on the pallet through artificial intelligence. Therefore, this paper uses the YOLACT deep learning method in artificial intelligence to study the detection and segmentation of the pallet in the carriage. Since human movement will affect the detection of goods and in order to exclude the influence of pallets outside the carriage, this paper also studies the detection and segmentation of the human body and the ground inside the carriage. Firstly, a data set for the detection and segmentation of the pallet, human body and ground inside the carriage is established, and then the training set of random segmentation is used for effective training to a certain extent, and the corresponding verification set is verified. After the training, the model is tested accordingly. The detection results show that the reasoning speed of YOLACT with resnet50 as the backbone is 14.6FPS and mAP is 27.2 under the condition of GTX 1660Ti.","PeriodicalId":412698,"journal":{"name":"2021 IEEE International Conference on Artificial Intelligence and Industrial Design (AIID)","volume":"18 4","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-05-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114025268","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 Passenger Flow Path Reduction of Urban Rail Transit Based on AFC Data and Transfer Estimation 基于AFC数据和换乘估计的城市轨道交通客流路径缩减研究

2021 IEEE International Conference on Artificial Intelligence and Industrial Design (AIID) Pub Date : 2021-05-28 DOI: 10.1109/AIID51893.2021.9456494

Y. Jiang, Wanyang Zuo, Yangchenmiao Cui

引用次数: 0

Research on construction site dust detection based on prior knowledge MinMax k-Means 基于先验知识MinMax k-Means的建筑工地粉尘检测研究

2021 IEEE International Conference on Artificial Intelligence and Industrial Design (AIID) Pub Date : 2021-05-28 DOI: 10.1109/AIID51893.2021.9456468

Qiao Jiang, Kun Zhang

{"title":"Research on construction site dust detection based on prior knowledge MinMax k-Means","authors":"Qiao Jiang, Kun Zhang","doi":"10.1109/AIID51893.2021.9456468","DOIUrl":"https://doi.org/10.1109/AIID51893.2021.9456468","url":null,"abstract":"With the rapid development of urbanization, promoting the process of industrialization has become the best breakthrough to accelerate economic development. The number of construction projects under construction is increasing gradually. In recent years, people are paying more and more attention to the impact of atmospheric particulate matter on the environment and human health. Construction dust is a by-product of open-air construction activities, which does great harm to the ecological environment and human health. It contributes 13.1 % [1]to urban PM2.5 pollution and is also one of the main sources of atmospheric pollutant PM10[2]. In order to timely detect construction site dust and improve the ability of government supervision departments to monitor construction dust pollution, a construction site dust detection method based on prior knowledge Minmax K-means clustering algorithm was proposed. In the process of clustering, the weight which is proportional to the variance in the cluster can be automatically corrected, and the priori knowledge is introduced to deal with the problem that the clustering results are sensitive to the initial position of the clustering center. In addition, the preprocessing adopts the method that the mean value of image blocks with dust is larger than that without dust, and scans the mean value matrix from vertical and horizontal directions to judge whether the image blocks have dust.","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":"129318627","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

Development of A Smart Lock System Based on Internet of Things and Cloud Platform 基于物联网和云平台的智能锁系统开发

2021 IEEE International Conference on Artificial Intelligence and Industrial Design (AIID) Pub Date : 2021-05-28 DOI: 10.1109/AIID51893.2021.9456578

Meigui Yin, Juan Huang, Hailang Chen

引用次数: 0

Bank Business Data Analysis System Based on FPGA Technology 基于FPGA技术的银行业务数据分析系统

2021 IEEE International Conference on Artificial Intelligence and Industrial Design (AIID) Pub Date : 2021-05-28 DOI: 10.1109/AIID51893.2021.9456536

Ji Meilin, Y. Liying, Cao Qixuan

{"title":"Bank Business Data Analysis System Based on FPGA Technology","authors":"Ji Meilin, Y. Liying, Cao Qixuan","doi":"10.1109/AIID51893.2021.9456536","DOIUrl":"https://doi.org/10.1109/AIID51893.2021.9456536","url":null,"abstract":"As a technology of programmable logic devices, FPGA has the advantages of low power consumption, multithreading parallel data processing, high integration, high speed and so on. It is a very effective acceleration tool. In recent years, with the rapid development of China's economy, the amount of data in the financial industry is more and more huge, the update is faster and faster, the fault tolerance rate is lower and lower, so the popularity of FPGA in the financial industry is imminent. In this paper, an iterative placement algorithm based on resource negotiation is adopted, and a fast routing algorithm based on new rerouting strategy and maze router is proposed, and a parallel FPGA routing algorithm based on multi-core processor is proposed for chip parallel processing data. Finally, this paper expounds the application of FPGA in the financial field from three aspects: the acquisition of real-time financial information on the network, the transmission of financial information and the processing mode of information, which improves the speed and accuracy of information acquisition and effectively promotes the development of socialist economy.","PeriodicalId":412698,"journal":{"name":"2021 IEEE International Conference on Artificial Intelligence and Industrial Design (AIID)","volume":"51 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":"114623965","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