检索结果-内蒙古大学图书馆

International Conference on Electronics, computers and Artificial Intelligence (ECAI)

作者： Pham Duc Dai Bui Thi Hai Linh Department of Control Engineering and Automation Thuyloi University Hanoi Vietnam

ISBN: (数字)9798350371154

ISBN: (纸本)9798350371161

Quadrotors have been applied to many areas. control of the quadrotor for tracking the desired trajectory is challenging. Several traditional control approaches using PID controllers have been applied to control UAV. Such the approach requires the model to be linearized. This paper proposed to apply the nonlinear model predictive control to guide the quadrotor while getting collision free by using the concept of the hyperplane moving constraints. To address the NMPC, the multiple shooting method has been applied to discretize the optimal control problem to the nonlinear program (NLP) and it is efficiently solved by the standard NLP solver. Numerical computation has been shown that the application of the multiple shooting method gives the more efficient NLP with a less number of optimization variables.

关键词： Trajectory tracking Optimal control Water quality Autonomous aerial vehicles Real-time systems Trajectory Optimization

来源：评论

学校读者我要写书评

暂无评论

Myocardial segmentation of 2D echocardiography based on the improved self-attention mechanism 2

Myocardial segmentation of 2D echocardiography based on the ...

引用

2nd International Conference on Machine Vision, Image Processing and Imaging Technology, MVIPIT 2024

作者： Li, Delong Sun, Yixin Han, Xue Dong, Suyu College of Computer and Control Engineering Northeast Forestry University Harbin China The Department of Ultrasound Harbin Medical University Cancer Hospital Harbin China

ISBN: (纸本)9798331543037

The measurement of different clinical indicators, such as the myocardial wall's thickness and the ventricle's volume, depends on accurately segmenting the left ventricle in 2D echocardiography. This segmentation is essential for making various clinical decisions, such as whether surgery is necessary. However, segmenting the myocardium requires clinical expertise and makes accurate segmenting time-consuming due to the poor quality of echocardiograms. It is essential to develop an automatic myocardial segmentation method. Some deep learning methods, especially the U-net structure, were proposed to support the automatic myocardium segmentation in echocardiography. The model must simultaneously capture the local and global dependency relationships in the ultrasound images for myocardial segmentation in echocardiography. Given the inherent attribute of local operation of convolution operations, this poses significant limitations for U-Net based on the traditional CNN as the basic architecture. For example, when dealing with complex myocardial textures and structures, we need to accurately identify the myocardium's global morphological features and overall structural patterns. Moreover, this locality may lead to deviations and errors when segmenting the boundary regions or the myocardial parts closely related to the surrounding tissues. Our primary focus will be redefining the skip connection using the attention mechanism. More integrated attention mechanisms can further enhance the segmentation effect of myocardial in echocardiography. Therefore, we integrated the cross-attention mechanism when concatenating features in the skip connection. Through conducting rigorous ablation studies on multiple echocardiography segmentation datasets, the performance of the proposed mechanism was proven. ©2024 IEEE.

关键词： Echocardiography

来源：评论

学校读者我要写书评

暂无评论

Artificial Intelligence Based Employee Attrition Analysis and Prediction 6

Artificial Intelligence Based Employee Attrition Analysis an...

引用

6th International Conference on Computing and Informatics, ICCI 2024

作者： Ozakca, Nazli Sila Bulus, Ali Cetin, Aydin Havelsan Inc.Command Control and Defence technologies Ankara Turkey Computer Engineering Department Gazi University Faculty of Technology Ankara Turkey

ISBN: (纸本)9798350373875

The use of classification models to predict the probability of an employee leaving the job can greatly improve the ability of human resources to intervene in a timely manner and rectify the situation to prevent attrition. After the so-called "The Great Resignation", which took place after the pandemic period, studies on attrition have increased in order to regain the lost workforce and increase the loyalty of existing employees. In Turkey, however, studies in this field remain insufficient. The aim of this study is to predict the possible loss of employees, to take relevant measures and to reduce the financial losses of companies. The study was made available as SaaS (Software as a Service) based in order to facilitate accessibility to the target audience. For the analysis phase, the columns in the data set were analyzed with Pandas and Scikit-Learn library. Exploratory Data Analysis was performed by visualizing the analyzed data with Plotly and Seaborn libraries. Various insights were obtained with these inferences. The data was subjected to pre-processing stages such as cleaning, missing data completion, scaling, feature selection, data set balancing, dimension reduction, etc. to make it useful. Logistic Regression, KNN, SVM, Desicion Tree, Random Forest, ADABoost and Naive Bayes were used to train the model. In order to enrich the data set and increase the efficiency of the model, artificial intelligence-based synthetic data generation (Data Augmentation) was performed. In case of missing columns in the trained model, KNN-Data Imputation, one of the missing data completion methods, was used. In the optimization process of the model, hyperparameter optimizations were performed to achieve maximum efficiency with improvements. 5-fold cross-validation prevented the model from over-learning. Performance was analyzed on the basis of Accuracy, Recall, Precision and F1-score metrics and the success criterion was determined as F1-Score. The model was presented as a web se

关键词： Efficiency

来源：评论

学校读者我要写书评

暂无评论

Two-Stage Representation Refinement Based on Convex Combination for 3-D Human Poses Estimation

IEEE Transactions on Artificial Intelligence

引用

IEEE Transactions on Artificial Intelligence 2024年第12期5卷 6500-6508页

作者： Chen, Luefeng Cao, Wei Zheng, Biao Wu, Min Pedrycz, Witold Hirota, Kaoru China University of Geosciences School of Automation Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China Ministry of Education Engineering Research Center of Intelligent Technology for Geo-Exploration Wuhan430074 China University of Alberta Department of Electrical and Computer Engineering EdmontonABT6G 2R3 Canada Macau University of Science and Technology Institute of Systems Engineering Taipa999078 China Istinye University Research Center of Performance and Productivity Analysis Istanbul34010 Turkey Tokyo Institute of Technology Yokohama226-8502 Japan

In the human pose estimation task, on the one hand, 3-D pose always has difficulty in dividing different 2-D poses if the view is limited;on the other hand, it is hard to reduce the lifting ambiguity because of the lack of depth information, it is an important and challenging problem. Therefore, two-stage representation refinement based on the convex combination for 3-D human pose estimation is proposed, in which the two-stage method includes a dense-spatial-temporal convolutional network and a local-to-refine network. The former is applied to determine the features between each video frame;the latter is used to get the different scales of pose details. It aims to address the difficulty of estimating 3-D human pose from 2-D image sequences. In such a way, it can better use the relations between every frame in the sequence of the pose video to produce more accurate results. Finally, we combine the above network with a block called convex combination to help refine the 3-D pose location. We test the proposed approach on both Human3.6m and MPII datasets. The result confirms that our method can achieve better performance than improved CNN supervision, a simple yet effective baseline, and coarse-to-fine volumetric prediction. Besides, a robustness test experiment is carried out for the proposed method while the input is interrupted. The result verifies that our method shows better robustness. © 2024 IEEE.

关键词： Convolution

来源：评论

学校读者我要写书评

暂无评论

Lidar-Visual-Inertial Odometry with Online Extrinsic Calibration

引用

Journal of Shanghai Jiaotong university(Science) 2023年第1期28卷 70-76页

作者：茅天阳赵文韬王景川陈卫东 Department of Automation Institute of Medical RoboticsShanghai Jiao Tong UniversityShanghai 200240China Key Laboratory of System Control and Information Processing of Ministry of Education Shanghai 200240China Shanghai Engineering Research Center of Intelligent Control and Management Shanghai 200240China

To achieve precise localization,autonomous vehicles usually rely on a multi-sensor perception system surrounding the mobile *** is a time-consuming process,and mechanical distortion will cause extrinsic calibration ***,we propose a lidar-visual-inertial odometry,which is combined with an adapted sliding window mechanism and allows for online nonlinear optimization and extrinsic *** the adapted sliding window mechanism,spatial-temporal alignment is performed to manage measurements arriving at different *** nonlinear optimization with online calibration,visual features,cloud features,and inertial measurement unit(IMU)measurements are used to estimate the ego-motion and perform extrinsic *** experiments were carried out on both public datasets and real-world *** indicate that the proposed system outperforms state-of-the-art open-source methods when facing challenging sensor-degenerating conditions.

关键词： autonomous vehicles multi-sensor fusion online calibration

来源：评论

学校读者我要写书评

暂无评论

Reinforcement Learning Behavioral control for Nonlinear Autonomous System

引用

IEEE/CAA Journal of Automatica Sinica 2022年第9期9卷 1561-1573页

作者： Zhenyi Zhang Zhibin Mo Yutao Chen Jie Huang the College of Electrical Engineering and Automation Fuzhou UniversityFuzhou 350108 the Key Laboratory of Industrial Automation Control Technology and Information Processing Education Department of Fujian ProvinceFuzhou 350108 G+Industrial Internet Institute Fuzhou UniversityFuzhou 350108China

Behavior-based autonomous systems rely on human intelligence to resolve multi-mission conflicts by designing mission priority rules and nonlinear *** this work,a novel twolayer reinforcement learning behavioral control(RLBC)method is proposed to reduce such dependence by trial-and-error ***,in the upper layer,a reinforcement learning mission supervisor(RLMS)is designed to learn the optimal mission *** with existing mission supervisors,the RLMS improves the dynamic performance of mission priority adjustment by maximizing cumulative rewards and reducing hardware storage demand when using neural *** the lower layer,a reinforcement learning controller(RLC)is designed to learn the optimal control *** with existing behavioral controllers,the RLC reduces the control cost of mission priority adjustment by balancing control performance and *** error signals are proved to be semi-globally uniformly ultimately bounded(SGUUB).Simulation results show that the number of mission priority adjustment and the control cost are significantly reduced compared to some existing mission supervisors and behavioral controllers,respectively.

关键词： Behavioral control mission supervisor nonlinear autonomous system reinforcement learning

来源：评论

学校读者我要写书评

暂无评论

Efficient multimodal cancelable biometric system based on steganography and cryptography

引用

Iran Journal of computer Science 2023年第2期6卷 109-121页

作者： Salama, Gerges M. El-Gazar, Safaa Nassar, Rana M. El-Shafai, Walid Khalaf, Ashraf A. M. El-Banby, Ghada M. Hamed, Hesham F. A. El-Samie, Fathi E. Abd Department of Electrical Engineering Faculty of Engineering Minia University Minia 61111 Egypt Department of Electronics and Electrical Communications Engineering Faculty of Electronic Engineering Menoufia University Menouf 32952 Egypt Security Engineering Laboratory Department of Computer Science Prince Sultan University Riyadh 11586 Saudi Arabia Department of Industrial Electronics and Control Engineering Faculty of Electronic Engineering Menoufia University Menouf 32952 Egypt Department of Electrical Engineering Faculty of Engineering Egyptian-Russian University Cairo Egypt Department of Information Technology College of Computer and Information Sciences Princess Nourah Bint Abdulrahman University Riyadh 84428 Saudi Arabia

Due to the development of hacking programs, it has become easy to penetrate systems. Hence, there is a need for strong security mechanisms. The use of traditional passwords has become insufficient to secure systems. Biometric authentication is now widely used for security applications, and it has proven to be superior compared to traditional authentication methods. However, two issues need to be considered in biometric systems. The first is not to keep biometric data in its original form in the database. If biometric traits are hacked, they will no longer be of use. Biometric data should be kept in cancelable forms for reuse. The second issue is the reliance on a single biometric, which limits the verification accuracy. This can be solved by using a multimodal biometric system. Using steganography and cryptography, this paper introduces a cancelable multimodal biometric system. As voiceprints, facial images, and fingerprint images are used. In this paper, the verification is performed through the Mel frequency cepstral coefficients (MFCCs) of the voiceprints. Steganography is used as a tool to secure features extracted from voiceprints by embedding them into the facial image using block-based singular value decomposition (BSVD). Double random phase encoding (DRPE) is utilized as an encryption algorithm to generate the final cancelable templates. To increase the level of system security, fingerprint images are used as random phase masks (RPMs). Verification is performed by estimating the correlation between registered and test MFCCs. The correlation value is then compared with a threshold value, which is calculated using the distribution curves for the genuine and imposter correlations. Equal error rate (EER) values close to zero and an area under the receiver operator characteristic curve (AROC) that is close to one are obtained from the simulation results, demonstrating the outstanding performance of the suggested system. The proposed system achieves good performan

关键词： BSVD Cancelable biometrics DRPE MFCCs

来源：评论

学校读者我要写书评

暂无评论

Adaptive Neural Network-Based Visual Target Tracking control for Omnidirectional Mobile Robots 49

Adaptive Neural Network-Based Visual Target Tracking Control...

引用

49th Annual Conference of the IEEE Industrial Electronics Society, IECON 2023

作者： Zhang, Zhonghao Ge, Shuzhi Sam Jiang, Wanyue Institute for Future School of Automation Qingdao University Qingdao China National University of Singapore Department of Electrical and Computer Engineering Singapore

ISBN: (纸本)9798350331820

To address the problem of ensuring the target is within the field of view when robot vision tracking, this paper designs an adaptive neural network-based trajectory tracking controller for the motion control of an omnidirectional mobile robot during target tracking. First, the desired orientation angle of the omnidirectional robot is designed based on the relative positions of the human and the robot, taking into account the limitations of the camera field of view. Subsequently, a kinematic model of the robot is designed considering skidding and sliding environmental disturbances, and an adaptive neural network control scheme is proposed to cope with the uncertainty of the disturbance parameters. Theoretical and experimental proof that the solution is feasible. Simulation results show that the proposed control scheme can perform the target tracking task. Finally, the feasibility and effectiveness of the control scheme are verified through practical experiments. © 2023 IEEE.

关键词： Target tracking

来源：评论

学校读者我要写书评

暂无评论

DialogNTM: Context Reconstruction in Multi-Turn Dialogue Generation using Neural Turing Machines

DialogNTM: Context Reconstruction in Multi-Turn Dialogue Gen...

引用

2024 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2024

作者： Zhao, Haohao Liu, Meiling Zhou, Jiyun Fu, Kaiquan College of Computer and Control Engineering Northeast Forestry University Harbin China Lieber Institute Johns Hopkins University Baltimore United States South Dakota State University Department of Electrical Engineering and Computer Science BrookingsSD United States

ISBN: (纸本)9781665410205

In actual conversational scenarios, we can often determine which parts of the previous dialogue are more critical based on the current inquiry. However, the existing contextual modeling methods often encode the query sentence and the dialogue history in a unified manner, which fails to effectively highlight the inference effect of the query sentence. Moreover, these methods typically process the dialogue history only at the information extraction level, neglecting the treatment of the context itself. In this paper, we propose a novel conversational context modeling technique called DialogNTM. Based on the guidance of the query sentence, the technology can effectively eliminate redundant information by reconstructing the representation of the context. Specifically, we have tweaked the memory and input flow of the Neural Turing Machine (NTM) to encode contextual information in memory and guide the read, write, and erase operations of memory through query sentence. This design simulates the human brain's dynamic retrieval and renewal mechanism of previous memories when dealing with current problems. We have conducted extensive experiments on three publicly available datasets to verify the effectiveness of the DialogNTM model. Compared to the benchmark model, DialogNTM showed significant performance improvements ranging from 11% to 73% across multiple automated evaluation metrics (3.52% to 8.68% in absolute terms). © 2024 IEEE.

关键词： Turing machines

来源：评论

学校读者我要写书评

暂无评论

Vision-Based Fixed-Time Uncooperative Aerial Target Tracking for UAV

引用

IEEE/CAA Journal of Automatica Sinica 2023年第5期10卷 1322-1324页

作者： Peng Sun Siqi Li Bing Zhu Zongyu Zuo Xiaohua Xia the Seventh Research Division Beihang UniversityBeijing 100191China the School of Automation Beijing Institute of TechnologyBeijing 100081China the Department of Electrical Electronic and Computer EngineeringUniversity of PretoriaPretoria 0002South Africa

Dear Editor,In this letter,a vision-based fixed-time control is proposed for an unmanned aerial vehicle(UAV)with actuator saturation to track an uncooperative *** fixed-time control is designed in backstepping *** rel... 详细信息

关键词： Fixed cooperative letter

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：