2022 IEEE 6th Advanced Information Technology, Electronic and Automation Control Conference (IAEAC )最新文献_第6页

Research on the causes of false positives in source code detection 源代码检测中误报原因的研究

2022 IEEE 6th Advanced Information Technology, Electronic and Automation Control Conference (IAEAC ) Pub Date : 2022-10-03 DOI: 10.1109/IAEAC54830.2022.9929466

Ranxin Gao, Min Li, Yue Sun, Sen Jing, Wei Chen, Xiaotian Xu

引用次数: 0

Multi-Scene Robust Speaker Verification System Built on Improved ECAPA-TDNN 基于改进ECAPA-TDNN的多场景鲁棒说话人验证系统

2022 IEEE 6th Advanced Information Technology, Electronic and Automation Control Conference (IAEAC ) Pub Date : 2022-10-03 DOI: 10.1109/IAEAC54830.2022.9929964

Xi Xuan, Rong Jin, Tingyu Xuan, Guolei Du, Kaisheng Xuan

{"title":"Multi-Scene Robust Speaker Verification System Built on Improved ECAPA-TDNN","authors":"Xi Xuan, Rong Jin, Tingyu Xuan, Guolei Du, Kaisheng Xuan","doi":"10.1109/IAEAC54830.2022.9929964","DOIUrl":"https://doi.org/10.1109/IAEAC54830.2022.9929964","url":null,"abstract":"In order to solve the problems of cross-domain, short speech, and noise interference in industrial application scenarios of speaker recognition, this paper proposes an improved ECAPA-TDNN for a multi-scene robust speaker verification system architecture-improved DD-ECAP A-TDNN.The design of the DD-ECAPA-TDNN architecture is inspired by the model ECAPA-TDNN, which has recently become popular in ASV systems. Firstly, we use FBanks to extract acoustic features, followed by the DD-SE-Res2Net Block proposed in this paper to capture local features efficiently. Finally, the output feature mapping of all DD-SE-Res2Net Blocks aggregated at multiple scales, and finally the ASP pooling operation is performed. The experiments were based on the VoxCeleb1-dev dataset, and SC-AAMSoftmax was used to train a speaker identification model for 1211 speakers. This DD-ECAPA-TDNN model was used as speaker embedding extractor to construct an automatic speaker verification (ASV) system. We used VoxMovies and VoxCeleb1-O evaluation sets to simulate three scenarios of cross-domain, short speech and noise interference, respectively, to evaluate the performance of the DD-ECAPA-TDNN system under multiple scenarios. The system achieves an EER of 2.51% on VoxCeleb1-O. The DD-ECAPA-TDNN system significantly outperforms the ECAPA-TDNN system in terms of recognition performance in multiple scenarios. Finally, our ablation experiments show that the DD-SE-Res2N et Block has a positive impact on the performance of the ASV system, as well as that the DD-ECAPA-TDNN can extract robust and accurate speaker embedding with good scene generalization.","PeriodicalId":349113,"journal":{"name":"2022 IEEE 6th Advanced Information Technology, Electronic and Automation Control Conference (IAEAC )","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129042016","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

Design of Dual-core Collaborative Computing Gateway for Geological Hazards 地质灾害双核协同计算网关设计

2022 IEEE 6th Advanced Information Technology, Electronic and Automation Control Conference (IAEAC ) Pub Date : 2022-10-03 DOI: 10.1109/IAEAC54830.2022.9929932

Liu Yang, Shukai Xie, Luofeng Jiang, Chuan Li, Xing Zhu

{"title":"Design of Dual-core Collaborative Computing Gateway for Geological Hazards","authors":"Liu Yang, Shukai Xie, Luofeng Jiang, Chuan Li, Xing Zhu","doi":"10.1109/IAEAC54830.2022.9929932","DOIUrl":"https://doi.org/10.1109/IAEAC54830.2022.9929932","url":null,"abstract":"The previous gateway for monitoring geological hazards often focuses on receiving and transmitting data, which means sending the data stream from sensor terminals to the cloud server as much as possible. However, with the increase in the types and number of sensor terminals in geological hazard monitoring sites, such a massive data transmission mode cannot meet the needs of monitoring geological hazards. Therefore, a dual-core collaborative computing gateway for geological hazards is developed. Based on the previous network topology of monitoring geological hazards, a collaborative computing method of MCU and 4G Cat1 communication module is designed to transmit the real-time data stream received by MCU to the 4G Cat1 module, realizing complex calculations, such as mathematical model implementation and data early warning. In addition, this method can reduce the data traffic from the device to the cloud server and relieve the pressure on the server's data processing. The experimental results show that compared with the previous geological hazards monitoring gateway, the data transmission volume is reduced by about 81%, and the power consumption of the gateway using Raspberry Pi 3B is reduced by about 30.6%.","PeriodicalId":349113,"journal":{"name":"2022 IEEE 6th Advanced Information Technology, Electronic and Automation Control Conference (IAEAC )","volume":"70 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129102073","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

Conditional Random Fields Based on Neiderreit Sequence Initialized Eagle Perching Optimizer 基于Neiderreit序列初始化的条件随机场鹰栖息优化器

2022 IEEE 6th Advanced Information Technology, Electronic and Automation Control Conference (IAEAC ) Pub Date : 2022-10-03 DOI: 10.1109/IAEAC54830.2022.9930085

Zhihan Yu, Yuning He, Mengyao Shi, Mengdi Zhen, Zan Yang, Dan Li, Wei Nai

{"title":"Conditional Random Fields Based on Neiderreit Sequence Initialized Eagle Perching Optimizer","authors":"Zhihan Yu, Yuning He, Mengyao Shi, Mengdi Zhen, Zan Yang, Dan Li, Wei Nai","doi":"10.1109/IAEAC54830.2022.9930085","DOIUrl":"https://doi.org/10.1109/IAEAC54830.2022.9930085","url":null,"abstract":"Conditional random field (CRF) is a spatial state model proposed by the probability graph school of thought, and it belongs to the undirected probability inference model in the area of probability graph model. CRF combines the advantages of several classical models in machine learning (ML) and plays an important role in solving the model parameters of ML algorithms which describe unconstrained optimization problems. However, CRF also have its own defects, for some functions, such as multi-modal non convex smooth objective functions, it is difficult for it to find the global optimal solution by using gradient dependent methods, and the solution process is easy to fall into local optimal solution. At present, many scholars have studied CRF related issues, but most of them have just tried to use CRF algorithm to solve specific application problems in various industries, there are few reports on the optimization of CRF algorithm itself, especially its solution process. Thus, in this paper, a derivative free optimization swarm intelligence method, namely Neiderreit sequence initialized eagle percolating optimizer (NSIEPO) has been proposed to replace the gradient dependent method in finding the global optimal solution. By numerical analysis, the effectiveness of the proposed algorithm has been verified.","PeriodicalId":349113,"journal":{"name":"2022 IEEE 6th Advanced Information Technology, Electronic and Automation Control Conference (IAEAC )","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131086414","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

Short-term wind speed prediction based on deep learning and intelligent optimization algorithm 基于深度学习和智能优化算法的短期风速预测

2022 IEEE 6th Advanced Information Technology, Electronic and Automation Control Conference (IAEAC ) Pub Date : 2022-10-03 DOI: 10.1109/IAEAC54830.2022.9929670

Peilong Guan, Zikun Wu

引用次数: 1

Multi-Agent Deep Deterministic Policy Gradient Algorithm Based on Classification Experience Replay 基于分类经验重播的多智能体深度确定性策略梯度算法

2022 IEEE 6th Advanced Information Technology, Electronic and Automation Control Conference (IAEAC ) Pub Date : 2022-10-03 DOI: 10.1109/IAEAC54830.2022.9929494

Xiao-Yan Sun, Jinchao Chen, Chenglie Du, Mengying Zhan

{"title":"Multi-Agent Deep Deterministic Policy Gradient Algorithm Based on Classification Experience Replay","authors":"Xiao-Yan Sun, Jinchao Chen, Chenglie Du, Mengying Zhan","doi":"10.1109/IAEAC54830.2022.9929494","DOIUrl":"https://doi.org/10.1109/IAEAC54830.2022.9929494","url":null,"abstract":"In recent years, multi-agent reinforcement learning has been applied in many fields, such as urban traffic control, autonomous UAV operations, etc. Although the Multi-Agent Deep Deterministic Policy Gradient (MADDPG) algorithm has been used in various simulation environments as a classic reinforcement algorithm, its training efficiency is low and the convergence speed is slow due to its original experience playback mechanism and network structure. The random experience replay mechanism adopted by the algorithm breaks the time series correlation between data samples. However, the experience replay mechanism does not take advantage of important samples. Therefore, the paper proposes a Multi-Agent Deep Deterministic Policy Gradient method based on classification experience replay, which modifies the traditional random experience replay into classification experience replay. Classified storage can make full use of important samples. At the same time, the Critic network and the Actor network are updated asynchronously, and the learned better Critic network is used to guide the Actor network update. Finally, to verify the effectiveness of the proposed algorithm, the improved algorithm is compared with the traditional MADDPG method in a simulation environment.","PeriodicalId":349113,"journal":{"name":"2022 IEEE 6th Advanced Information Technology, Electronic and Automation Control Conference (IAEAC )","volume":"84 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130743624","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

Fast power line detection based on semantic flow 基于语义流的电力线快速检测

2022 IEEE 6th Advanced Information Technology, Electronic and Automation Control Conference (IAEAC ) Pub Date : 2022-10-03 DOI: 10.1109/IAEAC54830.2022.9929610

Yang Liu, Ninglei Ouyang, Peng Gou, Wei Nie, Jing Liang

引用次数: 1

Research on human-vehicle gesture interaction technology based on computer visionbility 基于计算机视觉的人机手势交互技术研究

2022 IEEE 6th Advanced Information Technology, Electronic and Automation Control Conference (IAEAC ) Pub Date : 2022-10-03 DOI: 10.1109/IAEAC54830.2022.9929908

He Guo, Rui Zhang, Y. Li, Ying Cheng, Peng Xia

{"title":"Research on human-vehicle gesture interaction technology based on computer visionbility","authors":"He Guo, Rui Zhang, Y. Li, Ying Cheng, Peng Xia","doi":"10.1109/IAEAC54830.2022.9929908","DOIUrl":"https://doi.org/10.1109/IAEAC54830.2022.9929908","url":null,"abstract":"With the development of human-computer interaction technology, gesture recognition is becoming more and more important. At the same time, due to the rapid development of automotive intelligence, the introduction of human-computer interaction technology into intelligent vehicles has increasingly become an important work. Aiming at the problems of low accuracy, low recognition efficiency and weak anti-interference ability of previous gesture recognition applications in driving scenes. This paper presents an improved yolov5 algorithm. By adding the improved and optimized k-means++ clustering optimization algorithm, the problems of unstable clustering effect of K-means clustering algorithm in yolov5 model and slow convergence to large-scale data are solved. In addition, by combining the C3 module in the backbone network with the attention mechanism (CBAM), the effect of target gesture recognition under complex background is improved. Finally, the latest optimization method of loss function (EIOU) is added to the algorithm model to improve the accuracy of training convergence. The average recognition accuracy of the algorithm proposed in this paper is 4.8% higher than 88.19% of the original yolov5s algorithm when the intersection to union ratio threshold is 0.5 to 0.95. The practical availability of the improved gesture recognition algorithm is verified by the simulation scene based on ROS (robot operating system) and unity.","PeriodicalId":349113,"journal":{"name":"2022 IEEE 6th Advanced Information Technology, Electronic and Automation Control Conference (IAEAC )","volume":"25 8","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131693263","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 pulmonary nodule segmentation algorithm based on improved V-Net 基于改进V-Net的肺结节分割算法研究

2022 IEEE 6th Advanced Information Technology, Electronic and Automation Control Conference (IAEAC ) Pub Date : 2022-10-03 DOI: 10.1109/IAEAC54830.2022.9929520

Haibo Lin, Yunhao Zhang, Xuefeng Chen, Huan Wang, Lingzhi Xia

引用次数: 0

Forecasting of Short-term Tourism Demand Based on Multivariate Time Series Clustering and LSSVM 基于多元时间序列聚类和LSSVM的短期旅游需求预测

2022 IEEE 6th Advanced Information Technology, Electronic and Automation Control Conference (IAEAC ) Pub Date : 2022-10-03 DOI: 10.1109/IAEAC54830.2022.9929603

Fen Liu, Wei Wang

引用次数: 0