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arXiv 2025年

作者： Lin, Tao Wang, Qingwang Liang, Qiwei Tang, Minghua Sun, Yuxuan Faculty of Information Engineering and Automation Kunming University of Science and Technology Kunming China College of Mechatronics and Control Engineering Shenzhen University Shenzhen China

Shadow removal is challenging due to the complex interaction of geometry, lighting, and environmental factors. Existing unsupervised methods often overlook shadow-specific priors, leading to incomplete shadow recovery. To address this issue, we propose a novel unsupervised Frequency Aware Shadow Removal Network (FASR-Net), which leverages the inherent frequency characteristics of shadow regions. Specifically, the proposed Wavelet Attention Downsampling Module (WADM) integrates wavelet-based image decomposition and deformable attention, effectively breaking down the image into frequency components to enhance shadow details within specific frequency bands. We also introduce several new loss functions for precise shadow-free image reproduction: a frequency loss to capture image component details, a brightness-chromaticity loss that references the chromaticity of shadow-free regions, and an alignment loss to ensure smooth transitions between shadowed and shadow-free regions. Experimental results on the AISTD and SRD datasets demonstrate that our method achieves superior shadow removal performance. Copyright © 2025, The Authors. All rights reserved.

关键词： Wavelet decomposition

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Research on Collaborative Object Detection and Recognition of Autonomous Underwater Vehicle Based on YOLO Algorithm

Research on Collaborative Object Detection and Recognition o...

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第33届中国控制与决策会议

作者： TANG Leisheng XU Hongli WU Han TAN Dongxu Gao Lei Shengyang Institute of Automation Chinese Academy of Science SHENYANG JIANZHU UNIVERSITY Information & Control Engineering Faculty Northeastern University Shenyang Ligong University School of Automation and Electrical Engineering

Autonomous underwater vehicle(AUV) is an important tool for human to explore and research marine *** to the influence of underwater environment,it is impossible to realize the rapid detection and recognition of AUV and the recognition of cooperative *** solve this problem,underwater light vision and underwater image enhancement technology are proposed to realize the rapid detection and recognition of underwater vehicles,so as to realize the recognition of cooperative *** this paper,YOLO algorithm which has a good effect on target detection precision and the recognition speed is used to recognize the underwater vehicle on the Yolo *** the original data set,histogram equalization and CLAHE algorithm are used to enhance the *** are respectively loaded into the same training model and trained on the yolov2 and yolov3 *** analysis of the experimental results shows that the underwater image enhancement technology based on the YOLOv3 network and the CLAHE algorithm can meet the requirements of rapid recognition for underwater vehicle detection and recognition.

关键词： Underwater Vehicle YOLO Neural Network Real-time Detection Target Recognition

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Isochronous Temporal Metric for Neighbourhood Analysis in Classification Tasks

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SN Computer Science 2023年第6期4卷 1-12页

作者： Kumar, Amit Krishan Mai, Nguyễn Ngọc Tian, Ke Xia, Yuanqing Institute of Research and Development Duy Tan University Da Nang Vietnam Faculty of Electrical-Electronic Engineering Duy Tan University Da Nang Vietnam Faculty of Chinese Language School of Foreign Language Duy Tan University Da Nang Vietnam State Key Laboratory of Intelligent Control and Decision of Complex Systems School of Automation Beijing Institute of Technology Beijing China

Machine learning, classification, and clustering techniques use the distance functions to evaluate the proximity between data entries and deduce the best neighbouring element and the closest matching entry. The best neighbour is not only the closest neighbour but a neighbour that is quick to respond. In view of that, a time-based isochronous metric is introduced to evaluate the best neighbours and form linkages by grouping similar entities. The proposed method uses parametric equations of the fastest descent and solves the time variables for attributes localised in curved space–time. The time metric is compared with commonly used distance metrics for accuracy in classification and clustering using benchmark and commonly used datasets. The nearest-neighbour technique is used for evaluating classification accuracy, and an adjusted random index (ARI) is used to evaluate clustering. The proposed method shows better accuracy and ARI in comparison to distance functions. It also assigns better weights to attributes of the dataset and easily identifies repeated patterns in noisy time series data.

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Hardware in the Loop Test Using Infrastructure Based Emergency Trajectories for Connected Automated Driving 31

Hardware in the Loop Test Using Infrastructure Based Emergen...

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31st IEEE Intelligent Vehicles Symposium, IV 2020

作者： Pechinger, Mathias Schroer, Guido Bogenberger, Klaus Markgraf, Carsten Faculty of Electrical Engineering University of Applied Sciences Augsburg Germany Siemens Mobility GmbH Munich Germany Chair of Traffic Engineering and Control Technical University Munich Germany

The path towards safe and highly automated driving is still under development. Especially when it comes to safety aspects, industry and research struggle to reach the required standards. In this paper we suggest using vehicle to infrastructure communication to provide a new kind of safety fallback solution in case conventional automated driving systems fail. This proposal is verified in a Hardware in the Loop setup. A fault is injected to the motion planner of a connected automated vehicle. The vehicle's own computing platform fails to generate a trajectory. An emergency message is sent to the infrastructure which seamlessly takes over the motion planning task and provides a backup trajectory to the vehicle. The infrastructure's motion plan is processed by the vehicle's motion controller and guides the vehicle to a safe stopping position. The scenario is executed with our research vehicle driving in a parking lot on a virtual highway and stopping on the hard shoulder. Additionally, a virtual vehicle is placed in the setup, acting as an obstacle on the shoulder lane of the highway. The whole scenario is thoroughly tested and shows one possibility on how the infrastructure can contribute to a safe path towards highly automated driving. © 2020 IEEE.

关键词： Vehicles

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Motion primitives-based and Two-phase Motion Planning for Fixed-wing UAV

Motion primitives-based and Two-phase Motion Planning for Fi...

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International Conference on control, automation, Robotics and Vision (ICARCV)

作者： Zheng Tan Yang Lyu Hanchen Lu Quan Pan Faculty of Automation Northwestern Polytechnical University Xi'an China Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing Electro-Mechanical Engineering Institute Beijing China

ISBN: (纸本)9781665476881

We present an efficient two-phase approach to motion planning for fixed-wing Unmanned Aerial Vehicles (UAV) navigating in complex 3D air slalom environments. Firstly, in discrete 3D workspace, a global planner computer a obstacle-free path roughly which satisfies the kinematic constraints of the UAV. Given a coarse global path, a local planner generate a Dubins curve with collision avoidance based on the UAS's perception constraints, dynamic constraints and the collision perception information received. We also introduce a method of decoupling the horizontal and vertical motion directions of the fixed-wing UAV, realizing the 2D Dubins curve planning in 3D workspace, along with precomputed sets of motion primitives derived from the vehicle dynamics model in order to achieve high efficiency. Finally, the feasibility of two-phase 3D motion planning in appropriate FOV is experimentally demonstrated.

关键词： Solid modeling Three-dimensional displays Navigation Dynamics Organizations Kinematics Autonomous aerial vehicles

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Automatic-Scheduling-Integrated Computerized Maintenance Management System for Small and Medium Manufacturing Plant

Automatic-Scheduling-Integrated Computerized Maintenance Man...

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International Conference on Green Technology and Sustainable Development (GTSD)

作者： Ngoc-Huy Tran Xuan-Thuyen Le Department of Control & Automation Faculty of Electrical & Electronics Engineering Ho Chi Minh City University of Technology (HCMUT) VNU-HCM Ho Chi Minh City Vietnam Innovation F abLab Ho Chi Minh City University of Technology (HCMUT) VNU-HCM Ho Chi Minh City Vietnam

ISBN: (数字)9798350386073

ISBN: (纸本)9798350386080

Since the onset of the Fourth Industrial Revolution, modern industrial plants have become increasingly complex, leading to a growing demand for specialized information systems to manage their operations. Computerized Maintenance Management System (CMMS) is a popular tool which can be used to manage physical assets maintenance in a factory. While the current implementations of CMMS in small and medium specialized manufacturing plants improves many aspects of maintenance operations such as increased productivity, better planning, there are many enhancements that could be made in term of efficiency, extensibility, … This paper proposes a CMMS solution that, in addition to typical CMMS main features, focus on creating an open interface following ISA-95 for easy integration into other manufacturing management systems and enterprise level software, as well as improving user productivity through the use of automatic scheduling based on Tabu Search algorithm. The results from a plastic manufacturing plant indicate that the proposed solution can significantly reduce scheduling efforts while maintaining scheduling constraints and quality.

关键词： Productivity Job shop scheduling Processor scheduling Software algorithms Software Maintenance Sustainable development

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Social manufacturing pattern in the intelligent reform of the shoes and clothing industry 1

Social manufacturing pattern in the intelligent reform of th...

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1st IEEE International Conference on Digital Twins and Parallel Intelligence, DTPI 2021

作者： Cao, Yansong Wang, Yutong Dai, Juwu Zhu, Xihao Wang, Fei-Yue Macau Institute of Systems Engineering Macau University of Science and Technology China Institute of Automation Chinese Academy of Sciences The State Key Laboratory for Management and Control of Complex Systems Beijing China Ningbo Sanbody Intelligent Technology Co. LTD Ningbo China University of Nottingham Faculty of Science and Engineering Ningbo China

ISBN: (纸本)9781665433372

Along with economic globalization, the shoes and clothing market is undergoing huge changes and is facing increasing individualized demands. To realize personalized customization, we propose a social manufacturing pattern for the shoes and clothing industry. On the customer side, we collect costumer information with the help of 3D scanning and virtual fitting. On the production side, we replace human labor with intelligent production equipment. On the enterprise management side, we construct a cloud platform to realize source maximization. Through this social manufacturing pattern, we expect to accelerate the intelligent reform of the shoes and clothing industry. © 2021 IEEE.

关键词： Shoe manufacture

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A Novel Remaining Useful Life Prediction Model Based on Adaptive Feature Fusion and its Application to Rolling Bearings

SSRN

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SSRN 2024年

作者： Guo, Kai Ma, Jun Wu, Jiande Xiong, Xin Faculty of Information Engineering & Automation Kunming University of Science and Technology Kunming650500 China Yunnan International Joint Laboratory of Intelligent Control and Application of Advanced Equipment Kunming University of Science and Technology Kunming650500 China Yunnan Key Laboratory of Intelligent Systems and Computing Yunnan University Kunming650500 China

As a key component in the transmission system of high-speed trains, once a failure occurs, it will directly affect the safety of train operation. Therefore, it is of great significance to construct a degradation index that can comprehensively characterize the running state of bearings and establish a reliable remaining useful life model to ensure the safety of train operation. Aiming at the problems that the redundant features in the existing multi-feature fusion process affect the diagnosis performance and the spurious fluctuations phenomenon of the fusion features causes the inaccurate determination of the start fault time and leads to the low prediction accuracy of remaining useful life (RUL), A method based on adaptive feature fusion and autoregressive integrated moving average model is proposed for rolling bearings prediction. The research in this study demonstrates that by comparing and verifying with two sets of public data, the proposed method is effective in accurately identifying the features that are most sensitive to degradation trends, accurately determine the initial fault moment of bearings, achieve effective prediction of the RUL of bearings, and the related research results can provide reference basis for predictive maintenance of train bearings. © 2024, The Authors. All rights reserved.

关键词： Forecasting

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Efficient Time-Delay System Optimization with Auto-Configured Metaheuristics

Efficient Time-Delay System Optimization with Auto-Configure...

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IEEE International Conference on Systems, Man and Cybernetics

作者： Roman Senkerik Aleksander Byrski Hubert Guzowski Peter Janku Tomas Kadavy Zuzana Kominkova Oplatkova Radek Matusu Michal Pluhacek Libor Pekar Maciej Smolka Adam Viktorin Department of Informatics and Artificial Intelligence A.I. Lab Faculty of Applied Informatics Tomas Bata University in Zlin Czech Republic Department of Automation and Control Engineering Faculty of Applied Informatics Tomas Bata University in Zlin Czech Republic Institute of Computer Science AGH University of Science and Technology Krakow Poland

This paper presents an experimental study that compares the performance of four selected metaheuristic algorithms for optimizing a time delay system model. Time delay system models are complex and challenging to optimize due to their inherent characteristics, such as non-linearity, multi-modality, and constraints. The study includes an explanation of the choice and core functionality of the selected algorithms, which are both baseline and state-of-the-art variants of self-organizing migrating algorithm (SOMA), state-of-the-art variant from the Success-History-based Adaptive Differential Evolution family of algorithms, with emphasis on diverse search (DISH algorithm), and Covariance Matrix Adaptation Evolution Strategy (CMA-ES) algorithm. The hyperparameters of the metaheuristic algorithms were set using the iRace automatic algorithm configuration framework. The paper emphasizes the importance of metaheuristic algorithms in control engineering for time-delay systems to develop more effective and efficient control strategies and precise model identifications. The experimental results highlight the effectiveness of the state-of-the-art algorithms with specific adaptive mechanisms like population organization process, diverse search and adaptation mechanisms ensuring a gradual transition from exploration to exploitation. Overall, this study contributes to understanding the challenges and advantages of using metaheuristic algorithms in control engineering for time delay systems. The results provide valuable insights into the performance of modern metaheuristic algorithms and can help guide the selection of appropriate adaptive mechanisms of metaheuristics.

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Sustainability and Predictive Accuracy Evaluation of Gel and Embroidered Electrodes for ECG Monitoring

SSRN

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SSRN 2024年

作者： Othman, Ghada Ben Kumar, Atal Anil Hassine, Faten Ben Copot, Dana Sidhom, Lilia Kamavuako, Ernest N. Trabelsi, Mohamed Ionescu, Clara Mihaela Chihi, Inès Ghent University Department of Electromechanics Systems and Metal Engineering Research Group on Dynamical Systems and Control Tech Lane Science Park 125 Zwijnaarde9052 Belgium Department Of Engineering Faculty of Science Technology and Medicine University of Luxembourg Kirchberg Luxembourg Faculty of Sciences of Tunis Tunis Tunisia National Engineering School of Bizerte Carthage University Tunis LAPER- Faculty of Sciences of Tunis El Manar University Tunis Tunisia Technical University of Cluj-Napoca Department of Automation Memorandumului no. 28 Cluj-Napoca400114 Romania Department of Informatics King’s College London London United Kingdom Electronics and Communications Engineering Department Kuwait College of Science and Technology Kuwait City Kuwait

Despite standards on electrocardiogram (ECG) monitoring in medical diagnostics, signal acquisition is prone to noisy artefacts and rely greatly on the quality of skin contact and signal transducing interference. Electrodes, serving as indispensable conduits in ECG signal acquisition, act as the crucial interface between the human body and recording instrumentation. The usage of traditional gel electrodes may provoke skin irritation, by contrast, the advent of embroidered electrodes, a contemporary innovation, holds the promise of more comfort monitoring. However, the sustainability quotient and predictive precision of these novel electrodes require more in-depth investigation. This paper endeavors a comprehensive evaluation of both gel and embroidered electrodes concerning ECG signal acquisition. Simultaneously, the study aims to construct a polynomial regression model leveraging advanced machine learning (ML) tools. The inferred model predicts embroidered signals based on experimental data obtained from gel electrodes. The methodology encompasses systematic data collection, preprocessing, insightful analysis, and the application of data-driven techniques. The findings of this study highlight the viability of embroidered electrodes as a compelling alternative, transcending traditional paradigms. Employing ML tools, the developed model achieves predictive accuracy, reflected in robust R2 values extending up to 94.9%. © 2024, The Authors. All rights reserved.

关键词： Electrocardiograms

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