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An end-to-end instance segmentation method based on improved ConvNeXt V2

International Journal of Wireless and Mobile Computing 2024年第4期26卷 384-392页

作者： Wang, Wenlu Sun, Ying Xu, Manman Bai, Dongxu Huang, Li Zou, Chunlong Chen, Baojia Tang, Dalai Key Laboratory of Metallurgical Equipment and Control Technology of Ministry of Education Wuhan University of Science and Technology Hubei Wuhan China Research Centre for Biomimetic Robot and Intelligent Measurement and Control Wuhan University of Science and Technology Hubei Wuhan China Hubei Key Laboratory of Mechanical Transmission and Manufacturing Engineering Wuhan University of Science and Technology Hubei Wuhan China College of Computer Science and Technology Wuhan University of Science and Technology Hubei Wuhan China Hubei Province Key Laboratory of Intelligent Information Processing and Real-time Industrial System Wuhan University of Science and Technology Hubei Wuhan China College of Mechanical Engineering Hubei University of Automotive Technology Hubei Shiyan China Hubei Key Laboratory of Hydroelectric Machinery Design and Maintenance China Three Gorges University Hubei Yichang China School of Computer Information Management Inner Mongolia University of Finance and Economics Hohhot China

In order to improve the efficiency of indoor mobile robots in locating and segmenting environmental instances, an instance segmentation method based on RTMDet is proposed. Firstly, the more powerful ConvNeXt V2 is used as the backbone network of the model, which improves the performance of the existing RTMDet model. Subsequently, NAS-FPN is used as a converged network to detect the network at any given time. Finally, AdamW is used as the model optimiser, which effectively solves the problem of excessive memory occupation when updating parameters and improves the performance of the model. The proposed method obtains the highest evaluation index in all cases. After training and testing on the Cityscapes data set, the recognition accuracy reaches 65.0%. © 2024 Inderscience Enterprises Ltd.

关键词： Statistical tests

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Synchronously realizing high spatial resolution and precise location for fiber fault attenuation event detection

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Optics Letters 2025年第11期50卷 3732-3735页

作者： Liu, Hui Zhao, Tong Zhang, Mingjiang College of Physics and Optoelectronics Taiyuan University of Technology Taiyuan030024 China Key Laboratory of Advanced Transducers and Intelligent Control System Ministry of Education Taiyuan University of Technology Taiyuan030024 China Shanxi Key Laboratory of Precision Measurement Physics Taiyuan University of Technology Taiyuan030024 China

Attenuation events are common fault types in optical fiber links, which are very important to identify and accurately locate them with high resolution. However, research on achieving high spatial resolution for fiber fault event localization in the field of optical time-domain reflectometry (OTDR) mainly focuses on reflection events;the precise identification of attenuation events is rarely reported. A chaotic OTDR technique based on attenuation extraction–correlation compression integrative demodulation (AECCID) is proposed to realize high spatial resolution and high-precision localization of attenuation events in optical fiber links. The positioning process and principle of AECCID are analyzed and verified by simulation. The location and length of the attenuation event are precisely recognized according to the demodulated positions of the two correlation peaks. The spatial resolution is only determined by the full width at half maximum (FWHM) of the autocorrelation curve of chaotic lasers, which breaks through the limitation of wide pulse width on spatial resolution. The proof-of-concept experimental results show that when the pulse width is 1 µs and the detector bandwidth is 130 MHz, the spatial resolution is improved from 100 m to 0.87 m compared with conventional single-pulse OTDR. © 2025 Optica Publishing Group. All rights, including for text and data mining (TDM), Artificial Intelligence (AI) training, and similar technologies, are reserved.

关键词： Full width at half maximum

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A Nonsmooth Observer Based on Friction Model Compensation for Sensorless Permanent Magnet Synchronous Motor

A Nonsmooth Observer Based on Friction Model Compensation fo...

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第42届中国控制会议

作者： Zaishan Zhang Wenwu Zhu Ke Yu Xiangyu Wang Shihua Li School of Automation Southeast University Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education School of Electrical Engineering and Automation Hefei University of Technology

In this paper,a nonsmooth observer considering friction compensation is proposed for the sensorless permanent magnet synchronous motor(PMSM) to estimate the rotor position and *** is one of the main factors affecting the tracking accuracy of the motor at low speed,especially in the back and forth motion of the ***,based on the Stribeck friction model,a nonlinear friction model of the motor is ***,a nonsmooth observer with friction compensation is designed to estimate the position and speed of the rotor,and the lumped disturbance of the system at the same ***,the stability analysis of this nonsmooth observer is ***,the effectiveness of the proposed method is verified by the simulation results.

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Physics-Guided Human Motion Capture with Pose Probability Modeling

arXiv

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arXiv 2023年

作者： Ju, Jingyi Huang, Buzhen Zhu, Chen Li, Zhihao Wang, Yangang Southeast University China Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Nanjing China Huawei Noah's Ark Lab Canada

Incorporating physics in human motion capture to avoid artifacts like floating, foot sliding, and ground penetration is a promising direction. Existing solutions always adopt kinematic results as reference motions, and the physics is treated as a postprocessing module. However, due to the depth ambiguity, monocular motion capture inevitably suffers from noises, and the noisy reference often leads to failure for physics-based tracking. To address the obstacles, our key-idea is to employ physics as denoising guidance in the reverse diffusion process to reconstruct physically plausible human motion from a modeled pose probability distribution. Specifically, we first train a latent gaussian model that encodes the uncertainty of 2D-to-3D lifting to facilitate reverse diffusion. Then, a physics module is constructed to track the motion sampled from the distribution. The discrepancies between the tracked motion and image observation are used to provide explicit guidance for the reverse diffusion model to refine the motion. With several iterations, the physics-based tracking and kinematic denoising promote each other to generate a physically plausible human motion. Experimental results show that our method outperforms previous physics-based methods in both joint accuracy and success rate. More information can be found at https://***/Me-Ditto/Physics-Guided-Mocap. Copyright © 2023, The Authors. All rights reserved.

关键词： Kinematics

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A Noise Filter for Dynamic Vision Sensor Based on Spatiotemporal Correlation and Hot Pixel Detection

A Noise Filter for Dynamic Vision Sensor Based on Spatiotemp...

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International Conference on Autonomous Unmanned systems, ICAUS 2021

作者： Xu, Ninghui Zhao, Jiajia Ren, Yuan Wang, Lihui Key Laboratory of Micro-Inertial Instrument and Advanced Navigation Technology Ministry of Education School of Instrument Science and Engineering Southeast University Nanjing210096 China Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing100074 China

ISBN: (纸本)9789811694912

As a new type of neuromorphic sensor, the events-driven Dynamic Vision Sensor (DVS) has the advantages of low latency and wide dynamic range. The development of DVS overcomes the application limitations of traditional cameras in the field of high speed robots and autonomous driving. However, there are abundant unwanted noise events contained in the output of DVS, which severely affects the subsequent data-processing. To tackle the problem, a novel noise filter for DVS is proposed in this paper. Firstly, since the noise is composed of hot pixel events with high-frequency and random background activities, a time window is constructed to continuously detect hot pixels. Secondly, a spatiotemporal correlation-based denoising approach for each incoming event is conducted, while excluding its surrounding hot pixels, to avoid the negative effect caused by their high temporal correlation on the filter. Finally, the hot pixels are compensated with the events that are most probably to occur depending on the adjacent events, to achieve the completeness and precision of the output event stream. Experiments in different scenes demonstrate that the proposed noise filter can effectively eliminate the noise from the event stream of DVS and obviously outperforms the baseline method. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Pixels

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A long prediction horizon fcs-mpc algorithm with disturbance preview for three-phase inverters

A long prediction horizon fcs-mpc algorithm with disturbance...

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2023 Jiangsu Annual Conference on Automation, JACA 2023

作者： He, Xianghui Huang, Saijin Li, Guanjun Li, Haoyuan Wang, Xiangyu School of Automation Southeast University No. 2 Si Pai Lou Nanjing Jiangsu210096 China Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education China Jiangsu Engineering Technology Research Center for Energy Storage Conversion Application China Electric Power Research Institute Nanjing Jiangsu210003 China

ISBN: (纸本)9781839539848

This paper derives an efficient control algorithm to deal with the output voltage tracking control problem of threephase inverters with multiple disturbances (including parametric perturbations of filter, abrupt disturbances caused by load switching and harmonic disturbances brought by unbalanced loads and nonlinear loads). This accomplishment is realized through the long prediction horizon finite-control-set model predictive control (FCS-MPC) and the integration of a composite disturbance observer (CDO) and a disturbance preview model into the sphere decoding algorithm (SDA). This integration facilitates the estimation and prediction of future disturbance behaviors within the inverter system, which addresses the poor disturbance-rejection limitations inherent in conventional SDA approaches employed in previous studies. The algorithm also improves the dynamic performances of the output voltage. Simulations studies are illustrated to demonstrate the feasibility and effectiveness of the proposed control algorithm. Based on the presented results, the algorithm achieves good disturbance rejection capability and maintains small tracking error. © The Institution of Engineering & Technology 2023.

关键词： Disturbance rejection

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Single-Domain Generalization Combining Geometric Context Toward Instance Segmentation of Track Components

Single-Domain Generalization Combining Geometric Context Tow...

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International Joint Conference on Neural Networks (IJCNN)

作者： Shixiang Su Songlin Du Dezhou Wang Shuzhen Tong Xiaobo Lu School of Automation Southeast University Nanjing China Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Nanjing China School of Instrument Science and Engineering Southeast University Nanjing China

ISBN: (数字)9798350359312

ISBN: (纸本)9798350359329

A stable track components segmentation model should have consistent performance across a broad spectrum of railroad conditions, particularly in unfamiliar locations. Despite this, satisfying this requirement proves challenging when working with a limited track dataset, as there is a substantial domain shift between the given dataset and unobserved distributions. The goal of this paper is to improve the generalization ability of track component segmentation in situations where single-domain training data is available. Toward this end, a novel track component instance segmentation method combining the geometric context is proposed. First, we design an initial mask prediction head (IMPH) that utilizes predicted box output from the object detector to generate initial masks by merging the geometric priors of track components. Meanwhile, a multiscale feature fusion structure is introduced to encourage IMPH to better capture the geometric context. Then, a final mask refinement head (FMRH) is introduced to get higher quality masks with a geometry-gated aggregation strategy. On the basis of experiments on track datasets, it was determined that the heads can be incorporated with several types of detection frameworks and have demonstrated consistent generalization enhancements across multiple object detectors. Furthermore, our method substantially enhances segmentation performance on various unobserved domains.

关键词： Instance segmentation Geometry Accuracy Neural networks Merging Training data Detectors

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MADDPG: Multi-agent Deep Deterministic Policy Gradient Algorithm for Formation Elliptical Encirclement and Collision Avoidance 5th

MADDPG: Multi-agent Deep Deterministic Policy Gradient Algor...

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5th Chinese Conference on Swarm Intelligence and Cooperative control, CCSICC 2021

作者： Xu, Leixin Chen, Weibin Liu, Xiang Chen, Yang-Yang School of Automation Southeast University Nanjing210096 China Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Southeast University Nanjing210096 China Jiangsu Automation Research Institute Lianyungang222061 China China Tiesiju Civil Engineering Group Co. Ltd. Hefei230023 China

ISBN: (纸本)9789811939976

This paper considers the formation encirclement problem of multi-agent systems with collision avoidance, where the enclosing orbit is an ellipse, the target and the formation are dynamic. The novel rewards, that is the elliptical encirclement reward, the formation reward, the angular velocity reward and collision avoidance reward are designed and a reinforcement learning (RL) algorithm, that is multi-agent deep deterministic policy gradient (MADDPG), is designed based on the novel setting of rewards. Simulation results are given to show the validity of the proposed method. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Reinforcement learning

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Data-Driven Distributed Robust Consensus Kalman Filtering for Sensor Networks

Data-Driven Distributed Robust Consensus Kalman Filtering fo...

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2021 China Automation Congress, CAC 2021

作者： Zhou, Ziai Wu, Hao Zhang, Ya School of Automation Southeast University Nanjing China 210096 Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Nanjing China 210096

ISBN: (纸本)9781665426473

This paper mainly studies the distributed robust filtering problem for wireless sensor networks without knowing the variance of the driving noise and measuring noise. A distributed filtering algorithm based on leader-follower consensus strategy is developed. Firstly, from limited sampling data of noises, the empirical distribution of the noises which play a critical role in filtering is given. Secondly, by formulating the problem as a zero-sum game problem and using dynamic programming approach, an optimal distributed robust filtering policy with Wasserstein penalty for the leader is obtained. Then, by using an adaptively weighting average consensus protocol, the filtering algorithm for followers is given. The effectiveness of the proposed filter is demonstrated through simulations. © 2021 IEEE

关键词： Dynamic programming

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Anthropogenic monoterpenes aggravating ozone pollution

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National Science Review 2022年第9期9卷 178-185页

作者： Haichao Wang Xuefei Ma Zhaofeng Tan Hongli Wang Xiaorui Chen Shiyi Chen Yaqin Gao Ying Liu Yuhan Liu Xinping Yang Bin Yuan Limin Zeng Cheng Huang Keding Lu Yuanhang Zhang State Key Joint Laboratory of Environmental Simulation and Pollution Control State Environmental Protection Key Laboratory of Atmospheric Ozone Pollution ControlCollege of Environmental Sciences and Engineering Peking University School of Atmospheric Sciences Sun Yat-sen University Guangdong Provincial Observation and Research Station for Climate Environment and Air Quality Change in the Pearl River Estuary Key Laboratory of Tropical Atmosphere–Ocean System Ministry of Education Southern Marine Science and Engineering Guangdong Laboratory(Zhuhai) Institute of Energy and Climate Research IEK-8:TroposphereForschungszentrum Jülich Gmb H State Environmental Protection Key Laboratory of Formation and Prevention of the Urban Air Complex Shanghai Academy of Environmental Sciences Institute for Environmental and Climate Research Jinan University

Monoterpenes have been known to have a critical influence on air quality and climate change through their impact on the formation of fine *** we present field evidence that monoterpene oxidations largely enhanced local ozone production in a regional site in eastern *** observed monoterpene was most likely from biomass burning rather than biogenic emissions,as indicated by the high correlation with CO at night-time,and the observed ratio of these two species was consistent with previously determined values from biomass burning *** monoterpene oxidations were determined experimentally based on direct radical measurements,leading to a daily ozone enhancement of 4-18 parts per billion by volume（ppb）,which was 6%-16% of the total ozone production,depending on the speciation of *** demonstrates that the previously overlo oked anthropogenic monoterpenes make an important contribution to 03 production in eastern *** role could possibly be important at similar locations across China and other parts of the world that are characterized by massive emissions,especially where there are high *** results highlight that anthropogenic monoterpenes should be taken into account when proceeding with the coordinated mitigation of O3and particulate matter pollution.

关键词： monoterpenes ozone pollution biomass burning anthropogenic emissions radical chemistry

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