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Target tracking method of Siamese networks based on the broad learning system

CAAI Transactions on Intelligence Technology 2023年第3期8卷 1043-1057页

作者： Dan Zhang C.L.Philip Chen Tieshan Li Yi Zuo Nguyen Quang Duy Navigation College Dalian Maritime UniversityDalianChina Innovation and Entrepreneurship Education College Dalian Minzu UniversityDalianChina Computer Science and Engineering College South China University of TechnologyGuangzhouChina Department of Computer and Information Science Faculty of Science and TechnologyUniversity of MacaoMacaoChina School of Automation Engineering University of Electronic Science and Technology of ChinaChengduChina Faculty of Navigation Vietnam Maritime UniversityHaiphongVietnam

Target tracking has a wide range of applications in intelligent transportation,real‐time monitoring,human‐computer interaction and other ***,in the tracking process,the target is prone to deformation,occlusion,loss,scale variation,background clutter,illumination variation,etc.,which bring great challenges to realize accurate and real‐time *** based on Siamese networks promotes the application of deep learning in the field of target tracking,ensuring both accuracy and real‐time ***,due to its offline training,it is difficult to deal with the fast motion,serious occlusion,loss and deformation of the target during ***,it is very helpful to improve the performance of the Siamese networks by learning new features of the target quickly and updating the target position in time *** broad learning system(BLS)has a simple network structure,high learning efficiency,and strong feature learning *** at the problems of Siamese networks and the characteristics of BLS,a target tracking method based on BLS is *** method combines offline training with fast online learning of new features,which not only adopts the powerful feature representation ability of deep learning,but also skillfully uses the BLS for re‐learning and re‐*** broad re‐learning information is used for re‐detection when the target tracking appears serious occlusion and so on,so as to change the selection of the Siamese networks search area,solve the problem that the search range cannot meet the fast motion of the target,and improve the *** results show that the proposed method achieves good results on three challenging datasets and improves the performance of the basic algorithm in difficult scenarios.

关键词： broad learning system siamese network target tracking

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Measuring Fairness in AI Explanations with LEADR: Local Explanation Amplification Disparity Ratio 22nd

Measuring Fairness in AI Explanations with LEADR: Local Ex...

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22nd International Conference on Practical Applications of Agents and Multi-Agent Systems, PAAMS 2024

作者： Shoeibi, Niloufar DeGange, Jonathan Shoeibi, Nastaran Shoeibi, Ali Department of Computer Science and Automation Faculty of Sciences Universidad de Salamanca Salamanca Spain LLP Madrid Spain LLP Washington United States Mazandaran University of Science and Technology Babol Iran

ISBN: (纸本)9783031704147

We investigate the fairness of local explanations in AI models by comparing the mean explanations for privileged and unprivileged groups across various datasets and model types. Specifically, we train linear, multi-layer perceptron, and explainable boosting machine (EBM) models, on several key academic datasets. Local explanations are generated using both post-hoc methods (LIME), and direct methods - logistic regression, integrated gradients and EBM local feature importance. By comparing these explanations across models and methods, we introduce a new metric, the Local Explanation Amplification Disparity Ratio (LEADR), to measure disparities in feature attribution between privileged and unprivileged groups. Our preliminary findings suggest that transparent Whitebox models may exhibit a tendency to display greater disparity in bias than opaque Blackbox models. This insight encourages further research into bias mitigation strategies that are tailored to different algorithm types, with the goal of minimizing undesired bias in AI systems. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Logistic regression

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Improving Transparency in Romanian Public Procurement: Machine Learning to Classify Bidders and Validate Decisions 28th

Improving Transparency in Romanian Public Procurement: Machi...

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28th International Conference on Knowledge Based and Intelligent information and Engineering Systems, KES 2024

作者： Silaschi, Iasmina Oana Pop, Ioan Daniel Coroiu, Adriana Mihaela Automation and Computing Faculty Politehnica University Timisoara Timis300223 Romania Computer Science Department Babes-Bolyai University Cluj-Napoca40084 Romania

The primary objective of this research paper is to conduct a real-life case study, centred around a substantial dataset procured from numerous Romanian public procurement tenders. The study aims to classify the bidders according to their compatibility and suitability, an assessment determined by the accuracy of different machine learning models. The dataset used, is a vast body of information. More precisely, it includes data from a total of 289,472 enterprises, 47,974 contracting authorities and 42,474 tenders. The use of this extensive data set ensures a robust and comprehensive analysis, thus enabling the extraction of meaningful insights and facilitating the drawing of reliable conclusions. In the quest to rank bidders effectively, the performance of nine intelligent algorithms is evaluated and compared. The top-performing algorithms in this context appear to be Decision Trees, along with ensemble methods derived from them, namely the Random Forest Classifier and the Extra Trees Classifier. The outcomes of this study are satisfying, outperforming the metrics of a similar study conducted in the same domain. Given the potential concerns about Romania's integrity in dealing with contracting companies for public procurement auctions, this study holds significant value in its ability to validate the decision-making process employed in previous auctions. By casting light on the effectiveness of past procurement decisions and offering strategic guidance for future acquisitions, this research holds substantial implications for improving transparency and streamlining the bidder selection process within the public procurement area. Therefore, with potential for future work upon it, it promises to become a valuable addition in enhancing the integrity and efficiency of public procurement in Romania. © 2024 The Authors.

关键词： extra trees classifier labelled data precision public procurement random forest classifier

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Deep Learning in Distance Awareness Using Deep Learning Method 7th

Deep Learning in Distance Awareness Using Deep Learning Meth...

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7th International Conference on Microelectronics and Telecommunication Engineering, ICMETE 2023

作者： Hussein, Raghad I. Onaizah, Ameer N. Faculty of Pharmacy University of Kufa Najaf Iraq School of Automation Beijing Institute of Technology Zhongguancun Beijing100811 China Faculty of Computer Science and Mathematics University of Kufa Kufa Iraq

ISBN: (纸本)9789819995615

Recent studies have shown that deep learning does pretty well at reproducing 3D scenes using multiple-view images or videos. Nevertheless, these restorations do not expose the personalities of the items, and item identification is necessary for such a scene to work in augmented worlds or interactive features. The objects in a picture that have been reconstructed as a unified mesh are handled as a singular body rather than being seen as independent categories that can be engaged with or changed. Reconstructing an entity three-dimensional image from a two-dimensional image is challenging since the transformation from a visual scene to a picture is permanent and reduces a dimensionality. In addition to creating more exact shapes when compared with previous methodologies for mesh rebuilding from individual images, our approach exhibited improved achievement in initiating comprehensive meshes when compared to strategies using only inherent portrayal mesh rebuilding networks (for instance, neighborhood deep implicit functions). By applying the multi-modal instructional methods, this was done. Real-world facts were utilized to assess the effectiveness of the suggested method. The results showed that it might perform noticeably better than earlier methods for entity 3D scene rebuilding. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Mesh generation

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Improving Dendritic Neuron Model With Dynamic Scale-Free Network-Based Differential Evolution

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IEEE/CAA Journal of Automatica Sinica 2022年第1期9卷 99-110页

作者： Yang Yu Zhenyu Lei Yirui Wang Tengfei Zhang Chen Peng Shangce Gao College of Automation&College of Artificial Intelligence Nanjing University of Posts and TelecommunicationsNanjing 210023China Faculty of Engineering University of ToyamaToyama-shi 930-8555Japan Faculty of Electrical Engineering and Computer Science Ningbo UniversityNingbo 315211China Department of Automation School of Mechatronic Engineering and AutomationShanghai UniversityShanghai 200444China

Some recent research reports that a dendritic neuron model(DNM)can achieve better performance than traditional artificial neuron networks(ANNs)on classification,prediction,and other problems when its parameters are well-tuned by a learning ***,the back-propagation algorithm(BP),as a mostly used learning algorithm,intrinsically suffers from defects of slow convergence and easily dropping into local ***,more and more research adopts non-BP learning algorithms to train *** this paper,a dynamic scale-free network-based differential evolution(DSNDE)is developed by considering the demands of convergent speed and the ability to jump out of local *** performance of a DSNDE trained DNM is tested on 14 benchmark datasets and a photovoltaic power forecasting *** meta-heuristic algorithms are applied into comparison,including the champion of the 2017 IEEE Congress on Evolutionary Computation(CEC2017)benchmark competition effective butterfly optimizer with covariance matrix adapted retreat phase(EBOwithCMAR).The experimental results reveal that DSNDE achieves better performance than its peers.

关键词： Artificial neuron networks(ANNs) dendrite neuron network differential evolution(DE) scale-free network

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Reverse-Engineering Optimization Techniques of High-Level Synthesis: Practical Insights into Accelerating Applications with AMD-Xilinx Vitis

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IEEE Transactions on computer-Aided Design of Integrated Circuits and Systems 2025年

作者： Koronis, Jorge Garnica, Oscar Hidalgo, J. Ignacio Davila, Juan Lanchares Spain Department of Computer Architecture and Automation Faculty of Computer Science Universidad Complutense de Madrid Spain

Modern AI applications contain computationally expensive sections. Accelerator cards and tools like AMD Vitis HLS leverage high-level synthesis and hardware (HW) optimizations to create custom HW designs to accelerate ***, the learning curve is steep, even for those with previous knowledge of HW design, due to the complexity of the optimization techniques and limited information on their interactions and HW effects. This paper quantitatively analyzes the interactions of optimization techniques after reverse engineering Vitis' optimization directives, both in isolation and in *** 150 experiments were conducted to investigate three distinct goals: assessing pragma behavior and the rules governing pragma application and optimizations, modeling Vitis HLS latency estimates, and evaluating the impact of optimizations on design space exploration, specifically area and latency. These experiments involve different combinations and placements of optimizations in the loop and function hierarchy of the test bench. Our findings offer guidance on using Vitis pragmas and identify promising configurations for optimizing latency and area. © 1982-2012 IEEE.

关键词： Reverse engineering

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Laboratory Installation to Demonstrate the Advantages of a DC Network in a Smart Home 2

Laboratory Installation to Demonstrate the Advantages of a D...

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2nd International Conference on Technology Enhanced Learning in Higher Education, TELE 2022

作者： Kudryavtsev, Artem Zatsepina, Violetta Lipetsk State Technical University Automation and Computer Science Faculty Lipetsk Russia

ISBN: (纸本)9781665470070

This article analyzes the power supply system of a Smart Home based on a DC network. The question of the relevance of this technology, as well as the advantages of the system is considered. The load of a private house is determined by calculation method and the proof of effective integration of DC network into the energy structure of a residential building is provided. By the example of a laboratory installation the significance of the generator-storage-inverter-consumer system is demonstrated during the transition of some household appliances to direct current supply. The possibilities and prospects of implementing a laboratory model of smart home for training are analyzed, and algorithms for the control and interaction of devices are described. © 2022 IEEE.

关键词： Domestic appliances

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Smart Educational Robotics Laboratory Ecosystem for Remote Control of Robotic Manipulators Through Telepresence Technologies 2

Smart Educational Robotics Laboratory Ecosystem for Remote C...

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2nd International Conference on Technology Enhanced Learning in Higher Education, TELE 2022

作者： Kondratyev, Sergey Pikalov, Vladimir Muravyev, Artem Evseev, Alexei Lipetsk State Technical University Automation and Computer Science Faculty Lipetsk Russia

ISBN: (纸本)9781665470070

This paper discusses a smart laboratory robotics system designed to allow students remote connection and work with robotic manipulation devices and applications, as well as for teaching and conducting collaborative research projects in the field of electrical engineering and automation. A scheme of connecting all the necessary robotic devices and video cameras to the main server in the laboratory for the possibility of connecting to a remote desktop is presented. The developed solution for remotely connecting students to a physical robotic cell, which is connected to the lab server, is presented. Thanks to the proposed system, it was possible to conduct a debugging of new solutions for the control of robotic manipulation systems on a particular connected technological equipment. A telepresence system with real-time video streaming of physical robotic cell was developed to monitor the behavior of the robotic system remotely in order to understand the process of the connected devices clearly after the solution was uploaded to the robot controller. © 2022 IEEE.

关键词： Remote control

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Implementation of Educational Programs in the Field of Training IT Specialists on the Orders of Companies 2

Implementation of Educational Programs in the Field of Train...

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2nd International Conference on Technology Enhanced Learning in Higher Education, TELE 2022

作者： Galkin, Alexander Alexeev, Vladimir Lipetsk State Technical University Faculty of Automation and Computer Science Lipetsk Russia

ISBN: (纸本)9781665470070

The paper gives the description of the program of additional education for students in the field of information technology, implemented by the university in collaboration with IT companies. The following prerequisites for the development of such educational programs are noted: trends in the information technology market and the growing demand for qualified specialists. The needs of organizations in competencies of their employee lead to a personalized additional educational program for students developed by the university for the company. The conclusion of agreements between the student, the company and the university allows guaranteeing students - additional scholarships and employment, companies - reducing the adaptation time for new employees due to the availability of relevant competencies and getting to know the company in the learning process, the university - additional funding and developing the competencies of university teachers. An example of such a program implemented by the Lipetsk State Technical University in collaboration with RetailDriver LLC for students educated on Bachelor's programs in IT areas is given. © 2022 IEEE.

关键词： Students

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Development of Control System for Simulation and Verification of Four-Wheeled Mobile Robot Model with Shock-Absorbing Chassis 4

Development of Control System for Simulation and Verificatio...

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4th International Conference on Control Systems, Mathematical Modeling, automation and Energy Efficiency, SUMMA 2022

作者： Kondratyev, Sergey Pikalov, Vladimir Belokopytov, Ruslan Evseev, Alexei Lipetsk State Technical University Automation and Computer Science Faculty Lipetsk Russia

ISBN: (数字)9781665456593

ISBN: (纸本)9781665456593

The paper presents the design and analysis of a simulation model of the motion of a four-wheeled robot with a shock-absorbing chassis on a plane with the right pair of wheels on the ramp, drive on it and drive off the ramp and derive plots of the bending force acting on the upper suspension arm, force in the spring, moment on the rear wheel, angles of rotation of suspension hinges, speed of the cart and suspension levers on time. It was required to verify the coefficients of spring stiffness and spring length at rest from the spring calculation by the condition of locating the upper suspension arm perpendicular to the side surface of the robot when the robot is on the plane without external forces and torques, as well as by the condition of reducing the clearance of the robot. Based on the calculated forces for the suspension arms, a cross-section for the suspension arms is selected and their strength is calculated for the subsequent design of the physical robot. © 2022 IEEE.

关键词： Wheels

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