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International Conference on Control, Decision and Information Technologies (CoDIT)

作者： Amir Ismail Maroua Mehri Anis Sahbani Najoua Essoukri Ben Amara Ecole Nationale d’Ingénieurs de Sousse LATIS-Laboratory of Advanced Technology and Intelligent Systems Université de Sousse Sousse Tunisie Enova Robotics S.A. Novation City Technopôle de Sousse Sousse Tunisie CNRS Institute for Intelligent Systems and Robotics (ISIR) Sorbonne Université Paris France

ISBN: (数字)9798350373974

ISBN: (纸本)9798350373981

Automatic license plate recognition (ALPR) is a powerful tool for analyzing the growing number of vehicles in major cities worldwide. However, building datasets that accurately represent vehicles and license plates (LPs) is challenging, as most current datasets are specific to certain countries and do not provide a comprehensive representation. This remains particularly true for French LPs, where there is currently no publicly available dataset that covers a wide range of scenarios such as plate inclinations, varying lighting conditions, and changing weather. To address this issue, we present a benchmark suite called PGFLP 1.0, which includes more than 14k fully annotated LPs from several vehicle categories (e.g. cars, trucks, motorcycles). PGFLP 1.0 includes three annotation levels: rectangular boxes for the LP, four vertices of the LP region, and labels for the full LP sequence. Using PGFLP 1.0, we provide an experimental evaluation of the most recent ALPR approaches, assessing their ability to detect and recognize LPs. This work provides a useful benchmark in terms of accuracy and speed for current and future research efforts in ALPR.

关键词： Urban areas Buildings Motorcycles Lighting Benchmark testing Licenses Information technology License plate recognition Robots Meteorology

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Multiple Sensor Fusion-Based Positioning Robot for Steam Generator Inspection 2

Multiple Sensor Fusion-Based Positioning Robot for Steam Gen...

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2nd International Symposium on Sensor technology and Control, ISSTC 2023

作者： You, Jingwei Wei, Shouqi Wu, Xiong Sun, Jianquan Guilin University of Electronic Technology Department of Electrical Engineering Guilin541004 China Chinese Academy of Sciences Guangdong Provincial Key Lab of Robotics and Intelligent System Shenzhen Institutes of Advanced Technology Shenzhen518000 China SIAT-CUHK Joint Laboratory of Robotics and Intelligent Systems Shenzhen518000 China

ISBN: (纸本)9798350314465

Nuclear energy is presently the clean energy source most likely to massively displace fossil energy, and the secondary side of the steam generator is an important part of a nuclear power plant. Due to the small space of the secondary side of the steam generator and the confinement of the vessel, the precise positioning of the robot inside the steam generator cannot be achieved by a single sensor alone. This paper introduces a multi-sensor fusion steam generator secondary side inspection robot. Primary emphasis is on data fusion of multiple sensors, such as laser sensors, cameras, IMU, and wheel encoder. First of all, this paper integrates data from wheel encoder data and IMU data by using extended Kalman filtering (EKF), which decreases the drift error during the motion and enhances the robot positioning precision. Afterwards, we incorporate laser ranging sensors and camera picture data to enhance the overall spatial sensitivity of the robot through particle filtering algorithms. Experiments show that the robot works reliably and has high positioning accuracy. © 2023 IEEE.

关键词： Steam generators

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Improved Particle Swarm Optimization Algorithm for EIT Image Reconstruction 20

Improved Particle Swarm Optimization Algorithm for EIT Image...

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20th International Multi-Conference on systems, Signals and Devices, SSD 2023

作者： Kahouli, Oumayma Hafsa, Mariem Hellara, Hiba Bennour, Imed Eddine Essoukri Ben Amarax, Najoua Kanoun, Olfa University of Sousse National Engineering School of Sousse Department of Computer Science Sousse4023 Tunisia National Engineering School of Sousse Laboratory of Advanced Technology and Intelligent Systems Tunisia Technische Universität Chemnitz Laboratory of Measurement and Sensor Technology Chemnitz Germany University of Sfax Laboratory of Signals Systems Artificial Intelligence and Networks Digital Research Center of Sfax Tunisia

ISBN: (纸本)9798350332568

Electrical Impedance Tomography (EIT) is a clinical imaging technique that gained a lot of attention because it is a non-invasive and radiation-free method. To obtain an inner image of the domain under study, a specific number of electrodes is attached to the surface of the object, then through a pair of electrodes, a low alternative current is injected. Potentials produced by this injection are measured with the remaining electrodes. Based on these boundary voltages measurements, the inner conductivity can be inferred, thus the image is reconstructed. The focus of this paper is to overcome the major weakness of the EIT image reconstruction technique, which is the low spatial resolution of the reconstructed images caused by the non-linearity of EIT inverse problem. This paper considers this problem, an optimization problem that is solved using the Particle Swarm Optimization (PSO) meta-heuristic. A variant of the standard PSO is proposed and validated, first on a circular mesh composed of 686 triangles then on a lung mesh composed of 2707 triangles. © 2023 IEEE.

关键词： Electrodes

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Sea-Land Segmentation of Remote Sensing Images Based on SDW-UNet

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Computer systems Science & Engineering 2023年第5期45卷 1033-1045页

作者： Tianyu Liu Pengyu Liu Xiaowei Jia Shanji Chen Ying Ma Qian Gao The Information Department Beijing University of TechnologyBeijing 100124China School of Physics and Electronic Information Engineering Qinghai Minzu UniversityXining810000China Advanced Information Network Beijing Laboratory Beijing100124China Computational Intelligence and Intelligent Systems Beijing key Laboratory Beijing100124China Department of Computer Science University of Pittsburgh15260USA

Image segmentation of sea-land remote sensing images is of great importance for downstream applications including shoreline extraction,the monitoring of near-shore marine environment,and near-shore target *** mitigate large number of parameters and improve the segmentation accuracy,we propose a new Squeeze-Depth-Wise UNet(SDW-UNet)deep learning model for sea-land remote sensing image *** proposed SDW-UNet model leverages the squeeze-excitation and depth-wise separable convolution to construct new convolution modules,which enhance the model capacity in combining multiple channels and reduces the model *** further explore the effect of position-encoded information in NLP(Natural Language Processing)domain on sea-land segmentation *** have conducted extensive experiments to compare the proposed network with the mainstream segmentation network in terms of accuracy,the number of parameters and the time cost for *** test results on remote sensing data sets of Guam,Okinawa,Taiwan China,San Diego,and Diego Garcia demonstrate the effectiveness of SDW-UNet in recognizing different types of sea-land areas with a smaller number of parameters,reduces prediction time cost and improves performance over other mainstream segmentation *** also show that the position encoding can further improve the accuracy of model segmentation.

关键词： Sea-land segmentation UNet depth-wise separable convolution squeeze-excitation position encoding

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Mode-switching single-pixel imaging via a high-performance perovskite-Si dual-mode photodetector

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Photonics Research 2024年第12期12卷 2873-2880页

作者： YUJIN LIU DONGXU LIN JINGYANG XING HANYAN ZHAO HONGLING WAN HAO WANG ZHONG JI XUELI CHEN Innovation Center for Advanced Medical Imaging and Intelligent Medicine Guangzhou Institute of TechnologyXidian UniversityGuangzhou 510555China Shenzhen Key Laboratory of Intelligent Robotics and Flexible Manufacturing Systems Department of Mechanical and Energy EngineeringSUSTech Energy Institute for Carbon NeutralitySouthern University of Science and TechnologyShenzhen 518055China Center for Biomedical-Photonics and Molecular Imaging Advanced Diagnostic-Therapy Technology and Equipment Key Laboratory of Higher Education Institutions in Shaanxi ProvinceSchool of Life Science and TechnologyXidian UniversityXi’an 710126China

Visible–near-infrared(VIS-NIR)dual-mode imaging can expand the human perception ***,the development of dual-mode image sensors is still challenging due to complex fabrication processes and readout circuit ***,we design a simple-structured(perovskite-Au/Si/Ag)dual-mode *** unique asymmetric electrode design allows the device to support two operating modes at zero *** device exhibits a detection range covering 400–1100 nm under top illumination mode,with a peak specific detectivity of up to 5.56×1013 *** bottom illumination mode,the device demonstrates pronounced narrowband NIR response *** importantly,we develop a dual-mode single-pixel imaging system based on this device,bypassing the fabrication processes of high-density array image *** system exhibits excellent VISNIR dual-mode imaging results,effectively separating NIR and VIS information and enhancing infrared details in the fused ***,we discover that the system can effectively suppress ringing artifacts,achieving infrared information perception at a low sampling rate,which can accelerate the imaging speed by∼16 times(reduced from∼3.2 s to∼0.2 s).Our proposed dual-mode single-pixel imaging technology offers new means for material identification and intelligent perception.

关键词： mode illumination details

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Multiscale Bilateral Attention Fusion Network for Pansharpening

IEEE Transactions on Artificial Intelligence

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IEEE Transactions on Artificial Intelligence 2024年第11期5卷 5828-5843页

作者： Guo, Zhongyuan Li, Jiawei Lei, Jia Liu, Jinyuan Zhou, Shihua Wang, Bin Kasabov, Nikola K. Dalian University Key Laboratory of Advanced Design and Intelligent Computing Ministry of Education School of Software Engineering Dalian116622 China University of the Science and Technology Beijing School of Computer and Communication Engineering Beijing100083 China Dalian University of Technology School of Mechanical Engineering Dalian116024 China Auckland University of Technology Knowledge Engineering and Discovery Research Institute Auckland1061 New Zealand University of Ulster Intelligent Systems Research Center LondonderryBT48 7JL United Kingdom Bulgarian Academy of Sciences IICT Sofia1000 Bulgaria

High-resolution multispectral (HRMS) images combine spatial and spectral information originating from panchromatic (PAN) and reduced-resolution multispectral (LRMS) images. Pansharpening performs well and is widely used to obtain HRMS images. However, most pansharpening approaches determine the ratio of PAN and LRMS images through direct interpolation, which may introduce artifacts and distort the color of the fused results. To address this issue, an unsupervised progressive pansharpening framework, MSBANet, is proposed, which adopts a multistage fusion strategy. Each stage contains an attention interactive extraction module (AIEM) and a multiscale bilateral fusion module (MBFM). The AIEM extracts spatial and spectral features from input images and captures the correlations between features. The MBFM can efficiently integrate information from the AIEM and improve MSBANet context awareness. We design a hybrid loss function that enhances the ability of the fusion network to store spectral and texture details. In qualitative and quantitative experimental studies on four datasets, MSBANet outperformed state-of-the-art pansharpening techniques. The code will be released. © 2024 IEEE.

关键词： Data mining

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Exploring the nonlinear piezoresistive effect of 4HSiC and developing MEMS pressure sensors for extreme environments

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Microsystems & Nanoengineering 2023年第2期9卷 59-76页

作者： Chen Wu Xudong Fang Qiang Kang Ziyan Fang Junxia Wu Hongtao He Dong Zhang Libo Zha Bian Tian Ryutaro Maedai Zhuangde Jjang State Key Laboratory for Manufacturing Systems Engineering International Joint Laboratory for Micro/Nano Manufacturing and Measurement TechnologiesXian Jiaotong UniversityXian 710049China School of Mechanical Engineering Xian Jiaotong UniversityXi'an 710049China Shandong Laboratory of Yantai Advanced Materials and Green Manufacturing Yantai 265503China Xi'an Jiaotong University(Yantai)Research Institute for Intelligent Sensing Technology and System Xi'an Jiaotong UniversityXianChina HeBei Semiconductor Research Institute Shjiazhuang 050051China

Microelectromechanical system(MEMS)pressure sensors based on silicon are widely used and offer the benefits of miniaturization and high ***,they cannot easily withstand high temperatures exceeding 150 ℃ because of intrinsic material ***,we proposed and executed a systematic and full-process study of Sic-based MEMS pressure sensors that operate stably from-50 to 300 ℃.First,to explore the nonlinear piezoresistive effect,the temperature coefficient of resistance(TCR)values of 4H-SiC piezoresistors were obtained from-50 to 500 ℃.A conductivity variation model based on scattering theory was established to reveal the nonlinear variation ***,a piezoresistive pressure sensor based on 4H-SiC was designed and *** sensor shows good output sensitivity(3.38 mVN/MPa),accuracy(0.56%FS)and low temperature coefficient of sensitivity(TCS)(-0.067%FS/℃)in the range of-50 to 300 ℃.In addition,the survivability of the sensor chip in extreme environments was demonstrated by its anti-corrosion capability in H_(2)SO_(4) and NaOH solutions and its radiation tolerance under 5 W ***,the sensor developed in this work has high potential to measure pressure in high-temperature and extreme environments such as are faced in geothermal energy extraction,deep well dilling,aeroengines and gas turbines.

关键词： environments extreme nonlinear

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Exchange Strategies for Multi-Colony Ant Algorithms in Dynamic Environments 13

Exchange Strategies for Multi-Colony Ant Algorithms in Dynam...

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13th IEEE Congress on Evolutionary Computation, CEC 2024

作者： Mavrovouniotis, Michalis Li, Changhe Yazdani, Danial Handjimitsis, Diofantos Eratosthenes Centre of Excellence Limassol Cyprus Cyprus University of Technology Department of Civil Engineering and Geomatics Limassol Cyprus School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan China University of Technology Sydney Faculty of Engineering & Information Technology Sydney Australia

ISBN: (纸本)9798350308365

In dynamic optimization problems where optimal solutions change over time, traditional ant colony optimization (ACO) algorithms face limitations. This study explores the adaptation of multi-colony ACO algorithms, known for their enhanced search capabilities in stationary problems, to tackle optimization problems in dynamic environments. Various strategies for exchanging information between colonies, which is a critical factor influencing algorithm performance, are investigated. Using the dynamic traveling salesman problem as a foundation, we generate test cases to reflect real-world complexities. Our results on a set of problem instances reveal that the choice of communication strategy between colonies significantly impacts the adaptability and efficiency of multi-colony ACO algorithms in tracking moving optimum. © 2024 IEEE.

关键词： Ant colony optimization

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An accurate tuning model of spintronic memristor with different switching thresholds by logic judgment of domain wall motion 41

An accurate tuning model of spintronic memristor with differ...

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第41届中国控制会议

作者： Kun Wang Yajuan Hui Zhong Yang Xiangshui Miao School of Automation China University of Geosciences Hubei key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan National Lab for Optoelectronics Huazhong University of Science and Technology

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

Spintronic memristor possessing extraordinary advantages such as high-speed,low-power,highly scalable,and capable of constructing dynamic complex systems,which is a potential candidate for the next-generation memory *** many excellent models of spintronic memristor have been proposed,nonlinear model is not suitable for application analysis because of its complex *** this paper,an accurate tuning model of spintronic memristor with different switching thresholds by logic judgment of domain-wall motion is *** switching thresholds of current density are introduced to drive the domain-wall movement by judging the position of state value and real-time current density,which solves the general problems of boundary ***,by the simulation and verification via PSpice modeling,an accurate regulation of the resistance by voltage excitation is *** results pave the way for the applications of diversified circuit design for spintronic memristor.

关键词： Spintronic memristor Different switching thresholds SPICE model

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Approach For Probabilistic Semantic Big Data Indexing under an Uncertain Environment

Approach For Probabilistic Semantic Big Data Indexing under ...

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IEEE International Symposium on Innovations in intelligent systems and Applications (INISTA)

作者： Asma Omri Malika Jalouli Djamal Benslimane Mohammed Nazih Omri MARS Research Laboratory University of Sousse Tunisia Nationale d’Ingénieur de Sousse LATIS Laboratory of Advanced Technology and Intelligent Systems Université de Sousse Ecole Sousse Tunisie LIRIS Research Laboratory University Claude Bernard France

Indexing techniques are essential for efficiently storing and retrieving big data. Traditional indexing methods may not be suitable for uncertain environments due to their reliance on complete and accurate data. In such cases, probabilistic indexing techniques can be employed. These techniques assign probabilities to different values or attributes of the data, allowing for efficient retrieval even in the presence of uncertainty. Examples of probabilistic indexing techniques include inverted indexes with probabilistic weights and Bayesian networks. Handling uncertainty is a critical aspect of indexing big data in an uncertain environment. Our main objective in this paper is to propose a new method of semantic indexing of data in an uncertain environment. Basically, our proposed method is composed of two main parts: (i) a first part consists in processing the uncertain data in a textual document and, (ii) the second part consists in determining a new model of uncertain semantic *** developed a series of experiments to evaluate our proposed solution by comparing it to the approaches studied in the literature. The results found showed that our solution is more efficient.

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