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Multi-modal visual tracking:Review and experimental comparison

Computational Visual Media 2024年第2期10卷 193-214页

作者： Pengyu Zhang Dong Wang Huchuan Lu Faculty of Electronic Information and Electrical Engineering Dalian University of TechnologyDalian 116024Chin

Visual object tracking has been drawing increasing attention in recent years,as a fundamental task in computer *** extend the range of tracking applications,researchers have been introducing information from multiple modalities to handle specific scenes,with promising research prospects for emerging methods and *** provide a thorough review of multi-modal tracking,different aspects of multi-modal tracking algorithms are summarized under a unified taxonomy,with specific focus on visibledepth(RGB-D)and visible-thermal(RGB-T)***,a detailed description of the related benchmarks and challenges is *** experiments were conducted to analyze the effectiveness of trackers on five datasets:PTB,VOT19-RGBD,GTOT,RGBT234,and ***,various future directions,including model design and dataset construction,are discussed from different perspectives for further research.

关键词： visual tracking object tracking multi-modal fusion RGB-T tracking RGB-D trackin

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High-quality ghost imaging based on undersampled natural-order Hadamard source

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Chinese Physics B 2024年第9期33卷 404-411页

作者： Kang Liu Cheng Zhou Jipeng Huang Hongwu Qin Xuan Liu Xinwei Li Lijun Song School of Electronic Information Engineering Changchun UniversityChangchun 130022China School of Physics Northeast Normal UniversityChangchun 130024China College of Electronic and Information Engineering Changchun University of Science and TechnologyChangchun 130022China Jilin Engineering Laboratory for Quantum Information Technology Jilin Engineering Normal UniversityChangchun 130052China Changchun Institute of Technology Changchun 130012China

Improving the speed of ghost imaging is one of the main ways to leverage its advantages in sensitivity and imperfect spectral regions for practical *** of the proportional relationship between image resolution and measurement time,when the image pixels are large,the measurement time increases,making it difficult to achieve real-time ***,a high-quality ghost imaging method based on undersampled natural-order Hadamard is *** method uses the characteristics of the Hadamard matrix under undersampling conditions where image information can be fully obtained but overlaps,as well as deep learning to extract aliasing information from the overlapping results to obtain the true original image *** conducted numerical simulations and experimental tests on binary and grayscale objects under undersampling conditions to demonstrate the effectiveness and scalability of this *** method can significantly reduce the number of measurements required to obtain high-quality image information and advance application promotion.

关键词： ghost imaging natural-order Hadamard deep learning

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Remaining Life Prediction Method for Photovoltaic Modules Based on Two-Stage Wiener Process

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Energy engineering 2025年第1期122卷 331-347页

作者： Jie Lin Hongchi Shen Tingting Pei Yan Wu School of Electrical Engineering and Information Engineering Lanzhou University of TechnologyLanzhou730050China

Photovoltaic (PV) modules, as essential components of solar power generation systems, significantly influence unitpower generation *** service life of these modules directly affects these costs. Over time, the performanceof PV modules gradually declines due to internal degradation and external environmental *** cumulativedegradation impacts the overall reliability of photovoltaic power generation. This study addresses the complexdegradation process of PV modules by developing a two-stage Wiener process model. This approach accountsfor the distinct phases of degradation resulting from module aging and environmental influences. A powerdegradation model based on the two-stage Wiener process is constructed to describe individual differences inmodule degradation processes. To estimate the model parameters, a combination of the Expectation-Maximization(EM) algorithm and the Bayesian method is employed. Furthermore, the Schwarz information Criterion (SIC) isutilized to identify critical change points in PV module degradation trajectories. To validate the universality andeffectiveness of the proposed method, a comparative analysis is conducted against other established life predictiontechniques for PV modules.

关键词： Photovoltaic modules degradation stochastic processes lifetime prediction

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Synchronization Characterization of DC Microgrid Converter Output Voltage and Improved Adaptive Synchronization Control Methods

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Energy engineering 2025年第2期122卷 805-821页

作者： Wei Chen Xin Gao Zhanhong Wei Xusheng Yang Zhao Li School of Electrical Engineering and Information Engineering Lanzhou University of TechnologyLanzhou730050China

This paper deeply introduces a brand-new research method for the synchronous characteristics of DC microgrid bus voltage and an improved synchronous control *** method mainly targets the problem of bus voltage oscillation caused by the bifurcation behavior of DC microgrid ***,the article elaborately establishes a mathematical model of a single distributed power source with hierarchical *** this basis,a smallworld network model that can better adapt to the topology structure of DC microgrids is further ***,a voltage synchronization analysis method based on the main stability function is proposed,and the synchronous characteristics of DC bus voltage are deeply studied by analyzing the size of the minimum non-zero *** view of the situation that the line coupling strength between distributed power sources is insufficient to achieve bus voltage synchronization,this paper innovatively proposes a new improved adaptive controller to effectively control voltage *** the convergence of the designed controller is strictly proved by using Lyapunov’s stability ***,the effectiveness and feasibility of the designed controller in this paper are fully verified through detailed simulation *** comparative analysis with the traditional adaptive controller,it is found that the newly designed controller can make the bus voltages of each distributed power source achieve synchronization more quickly,and is significantly superior to the traditional adaptive controller in terms of anti-interference performance.

关键词： DC microgrid bifurcation small-world network voltage synchronization improved adaptive control

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Thermogalvanic hydrogel-based e-skin for self-powered on-body dual-modal temperature and strain sensing

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Microsystems & Nanoengineering 2024年第2期10卷 293-302页

作者： Zhaosu Wang Ning Li Xinru Yang Zhiyi Zhang Hulin Zhang Xiaojing Cui College of Electronic Information and Optical Engineering Taiyuan University of TechnologyTaiyuan030024China College of Materials Science and Engineering Taiyuan University of TechnologyTaiyuan030024China School of Physics and Information Engineering Shanxi Normal UniversityTaiyuan030031China

Sensing of both temperature and strain is crucial for various diagnostic and therapeutic ***,we present a novel hydrogel-based electronic skin(e-skin)capable of dual-mode sensing of temperature and *** thermocouple ion selected for this study is the iodine/triiodide(I−/I3−)redox couple,which is a common component in everyday *** leveraging the thermoelectric conversion in conjunction with the inherent piezoresistive effect of a gel electrolyte,self-powered sensing is achieved by utilizing the temperature difference between the human body and the external *** composite hydrogels synthesized from polyvinyl alcohol(PVA)monomers using a simple freeze‒thaw method exhibit remarkable flexibility,extensibility,and adaptability to human *** incorporation of zwitterions further augments the resistance of the hydrogel to dehydration and low temperatures,allowing maintenance of more than 90%of its weight after 48 h in the *** its robust thermal current response,the hydrogel was encapsulated and then integrated onto various areas of the human body,including the cheeks,fingers,and ***,the detection of the head-down state and the monitoring of foot movements demonstrate the promising application of the hydrogel in supervising the neck posture of sedentary office workers and the activity *** successful demonstration of self-powered on-body temperature and strain sensing opens up new possibilities for wearable intelligent electronics and robotics.

关键词： hydrogel modal utilizing

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Beyond Performance of Learning Control Subject to Uncertainties and Noise: A Frequency-Domain Approach Applied to Wafer Stages

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IEEE/CAA Journal of Automatica Sinica 2025年第1期12卷 198-214页

作者： Fazhi Song Ning Cui Shuaiqi Chen Kai Zhang Yang Liu Xinkai Chen Jiubin Tan IEEE the Center of Ultra-precision Optoelectronic Instrument Engineering Harbin Institute of Technology the Key Laboratory of Ultra-Precision Intelligent Instrumentation Ministry of Industry and Information Technology the State Key Laboratory of Precision Electronic Manufacturing Technology and Equipment Guangdong University of Technology the Center of Ultraprecision Optoelectronic Instrument Engineering Harbin Institute of Technology the Key Laboratory of UltraPrecision Intelligent Instrumentation Ministry of Industry and Information Technology the Department of Electronic and Information Systems Shibaura Institute of Technology

The increasingly stringent performance requirement in integrated circuit manufacturing, characterized by smaller feature sizes and higher productivity, necessitates the wafer stage executing a extreme motion with the accuracy in terms of nanometers. This demanding requirement witnesses a widespread application of iterative learning control(ILC), given the repetitive nature of wafer scanning. ILC enables substantial performance improvement by using past measurement data in combination with the system model knowledge. However, challenges arise in cases where the data is contaminated by the stochastic noise, or when the system model exhibits significant uncertainties, constraining the achievable performance. In response to this issue, an extended state observer(ESO) based adaptive ILC approach is proposed in the frequency *** being model-based, it utilizes only a rough system model and then compensates for the resulting model uncertainties using an ESO, thereby achieving high robustness against uncertainties with minimal modeling effort. Additionally, an adaptive learning law is developed to mitigate the limited performance in the presence of stochastic noise, yielding high convergence accuracy yet without compromising convergence speed. Simulation and experimental comparisons with existing model-based and data-driven inversion-based ILC validate the effectiveness as well as the superiority of the proposed method.

关键词： Extended state observer learning control model uncertainties motion control stochastic noise

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Accurate crop disease identification and classification in smart agriculture using a three-tier model and optimized fully conventional network

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Multimedia Tools and Applications 2025年第5期84卷 2539-2564页

作者： Rai, Ruchika Bansal, Pratosh Research Scholar Department of Information Technology Institute of Engineering and Technology Devi Ahilya Vishwavidyalaya MP Indore India Professor Department of Information Technology Institute of Engineering and Technology Devi Ahilya Vishwavidyalaya MP Indore India

Identification and classification of crop diseases are essential for efficient agricultural management because they allow early procedures to reduce crop losses and boost yields. Reduced food production, significant crop damage, and financial losses might result from inaccurate or delayed disease identification. To address these challenges, this work focuses on developing a hybrid deep-learning approach for the detection and classification of crop diseases. By integrating advanced techniques from deep learning, this model aims to enhance the accuracy and efficiency of disease identification in smart agriculture systems. The proposed model comprises four main phases: data collection, pre-processing, segmentation, feature extraction, feature selection, and disease detection and classification. Gaussian-adaptive bilateral filters are utilised in the pre-processing stage to reduce noise and blur, and histogram equalisation techniques are employed to improve the quality of the images. The segmentation step utilizes the Optimized Fully Convolutional Network (FCN) to isolate plant leaves from the background, while fine-tuning the model using the hybrid optimization approach Eclectic Harmony Optimization (EHO) ensures accurate differentiation of healthy and diseased areas. Feature extraction involves employing texture analysis techniques and shape descriptors to capture distinct characteristics of crop diseases. The proposed model is implemented using PYTHON. The proposed model outperformed advanced methods with an accuracy of 98.93%, demonstrating its competitive performance in identifying agricultural diseases. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024.

关键词： Adaptive filtering

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Intelligent Trajectory Control of Sampling Robotic Arm on Bidirectional LSTM Neural Network

Journal of Network Intelligence

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Journal of Network Intelligence 2025年第1期10卷 220-234页

作者： Xu, Jin-Yu Li, Ze-Ya Li, Zhou-Rong Li, Clement School of Electrical and Information Engineering Hubei University of Automotive Technology Shiyan442002 China College of Electronic Information Chongqing Institute of Engineering Chongqin400056 China College of Information Technology Waikato Institute of Technology Hamilton3240 New Zealand

A sampling robotic arm usually consists of multiple joints, allowing the arm to perform various motions and actions in three-dimensional space. Aiming at the problems of low sampling accuracy and poor motion smoothness in the work of the sampling robotic arm control system, this paper proposes an intelligent trajectory control method for the sampling robotic arm based on bidirectional LSTM neural network. Firstly, the kinematic model of the sampling robotic arm is established by analysing the interrelationships of the joints of the sampling robotic arm, and the kinematic analysis is completed by using the D-H method. Then, a Bidirectional Time-aware LSTM (Bi-T-LSTM) combined with Self-encoder is proposed. A bi-directional autoencoder is constructed using the time-aware LSTM unit, which combines the forward T-LSTM and the backward T-LSTM, in order to better capture the bi-directional trajectory information. Finally, a Self-encoder Bi-T-LSTM neural network controller is designed based on the sampled robotic arm kinematic model. The neural network controller is used to virtually control the inputs to compensate for the unknown mechanical system dynamics. The sampling robotic arm is simulated using Matlab/Simulink Simscape-Multibody and Simscape-Fluids simulation platforms. The simulation results show that the proposed intelligent trajectory control algorithm can help the robotic arm to optimise the trajectory planning more efficiently, achieve good position control, and ensure that the system output does not exceed the preset range. © 2025, Taiwan Ubiquitous information CO LTD. All rights reserved.

关键词： MATLAB

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Weighted sum power maximization for STAR-RIS-aided SWIPT systems with nonlinear energy harvesting

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Science China(information Sciences) 2024年第10期67卷 343-358页

作者： Weiping SHI Cunhua PAN Feng SHU Yongpeng WU Jiangzhou WANG Yongqiang BAO Jin TIAN School of Network and Communication Nanjing Vocational College of Information Technology National Mobile Communications Research Laboratory Southeast University School of Information and Communication Engineering Hainan University School of Electronic and Optical Engineering Nanjing University of Science and Technology Shanghai Key Laboratory of Navigation and Location Based Services Shanghai Jiao Tong University School of Engineering University of Kent School of Information and Communication Engineering Nanjing Institute of Technology Engineering School of Networks and Telecommunications Jinling Institute of Technology

The conventional reconfigurable intelligent surface(RIS) is limited to reflecting incident signals,thereby imposing constraints on the placement of the transmitter and receiver, which hinders achieving comprehensive signal coverage across an entire area. This paper investigates a simultaneously transmitting and reflecting(STAR)-RIS-aided simultaneous wireless information and power transfer(SWIPT) system with a nonlinear energy harvesting model under three different RIS transmission protocols: energy splitting(ES),time switching(TS), and mode switching(MS). The objective of this paper is to maximize the weighted sum power(WSP) of all energy harvesting receivers(EHRs) while ensuring fairness in the collected power among them. This is achieved by jointly optimizing the transmit beamforming at the base station(BS)and the transmission and reflection coefficients at the STAR-RIS, subject to rate constraints for information decoding receivers(IDRs), transmit power constraint at the BS, and coefficient constraints of each element at the STAR-RIS corresponding to the three protocols. Solving this optimization problem poses challenges because of the complicated objective function and numerous coupled optimization variables of the ES STAR-RIS. To address this complexity, an efficient alternating optimization(AO) approach is proposed as an iterative solution method that achieves suboptimal results. The AO algorithm is then extended to MS STAR-RIS and TS STAR-RIS. Specifically, for MS STRA-RIS, binary constraints in the STAR-RIS coefficient optimization subproblem are handled using the first-order approximation technique along with the penalty function method. For TS STAR-RIS, apart from optimizing BS transmit beamforming and STAR-RIS coefficients subproblems, the transmission and reflection time allocation of STAR-RIS also needs *** findings demonstrate that compared to conventional RIS-aided systems, utilizing three different protocols in a STAR-RIS-aided sy

关键词： STAR-RIS beamforming SWIPT alternating optimization nonlinear energy harvesting

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Robust DOA estimation and tracking for integrated sensing and communication massive MIMO OFDM systems

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Science China(information Sciences) 2023年第10期66卷 278-296页

作者： Kui XU Xiaochen XIA Chunguo LI Wei XIE Jie LIU Rangang ZHU Huasen HE College of Communications Engineering Army Engineering University of PLA School of Information Science and Engineering Southeast University School of Electronic Countermeasures National University of Defense Technology School of Information Science and Technology University of Science and Technology of China

In this paper, we propose a robust direction-of-arrival(DOA) estimation and tracking scheme for a massive multiple input multiple output(MIMO) orthogonal frequency-division multiplexing(OFDM)system using integrated sensing and communication(ISAC). First, a frame structure is designed to enable integrated DOA estimation and tracking, as well as data transmission. Then, coherent combining and multipath combining methods are proposed as pilot signal preprocessing methods for robust DOA estimation and tracking. Finally, for ISAC massive MIMO-OFDM systems, a fast Fourier transform(FFT) algorithmbased robust DOA estimator design is proposed, including a preamble-based initial DOA estimation scheme and an embedded pilot-based DOA tracking scheme. The simulation results demonstrate that the proposed robust DOA estimation and tracking method can obtain accurate DOA estimation even when the signal-tonoise ratio is low. Furthermore, the estimation performance outperforms the conventional multiple signal classification(MUSIC) and estimation of signal parameters via rotational invariance technique(ESPRIT)methods.

关键词： integrated sensing and communication massive multiple input multiple output (MIMO) orthogonal frequency-division multiplexing (OFDM) direction-of-arrival (DOA) estimation and tracking frame structure and pilot sequence

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