检索结果-内蒙古大学图书馆

17th Asian Conference on Computer Vision, ACCV 2024

作者： Jiao, Siyi Zeng, Wenzheng Gao, Changxin Sang, Nong Key Laboratory of Image Processing and Intelligent Control School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan China

ISBN: (纸本)9789819609710

Interactive portrait matting refers to extracting the soft portrait from a given image that best meets the user’s intent through their inputs. Existing methods often underperform in complex scenarios, mainly due to three factors. (1) Most works apply a tightly coupled network that directly predicts matting results, lacking interpretability and resulting in inadequate modeling. (2) Existing works are limited to a single type of user input, which is ineffective for intention understanding and also inefficient for user operation. (3) The multi-round characteristics have been under-explored, which is crucial for user interaction. To alleviate these limitations, we propose DFIMat, a decoupled framework that enables flexible interactive matting. Specifically, we first decouple the task into 2 sub-ones: localizing target instances by understanding scene semantics and the flexible user inputs, and conducting refinement for instance-level matting. We observe a clear performance gain from decoupling, as it makes sub-tasks easier to learn, and the flexible multi-type input further enhances both effectiveness and efficiency. DFIMat also considers the multi-round interaction property, where a contrastive reasoning module is designed to enhance cross-round refinement. Another limitation for multi-person matting task is the lack of training data. We address this by introducing a new synthetic data generation pipeline that can generate much more realistic samples than previous arts. A new large-scale dataset SMPMat is subsequently established. Experiments verify the significant superiority of DFIMat. With it, we also investigate the roles of different input types, providing valuable principles for users. Our code and dataset will be public. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Large datasets

来源：评论

学校读者我要写书评

暂无评论

Adaptive Event-Triggered control With Sampled Transmitted Output and controller Dynamics

引用

IEEE Transactions on control of Network Systems 2025年

作者： Zuo, Gewei Zhu, Lijun Huazhong University of Science and Technology School of Artificial Intelligence and Automation Wuhan430072 China Key Laboratory of Imaging Processing and Intelligence Control China

The event-triggered control with intermittent output can reduce the communication burden between the controller and plant sides over the network. It has been exploited for adaptive output feedback control of uncertain nonlinear systems in the literature;however, the controller must partially reside at the plant side where computation capacity is required. In this paper, all controller components are moved to the controller side, and their dynamics use sampled states rather than continuous ones with the benefit of directly estimating the next triggering instance of some conditions and avoiding constantly checking the event condition at the controller side. However, these bring two major challenges. First, the virtual input designed in the dynamic filtering technique for stabilization is no longer differentiable. Second, the plant output is sampled to transmit at the plant side and sampled again at the controller side to construct the controller, and the two asynchronous samplings make the analysis more involved. This paper solves these two issues by introducing a new state observer to simplify the adaptive law, a set of continuous companion variables for stability analysis, and a new lemma quantifying the error bound between actual output signal and sampled transmitted output. It is theoretically guaranteed that all internal signals in the closed-loop system are semiglobally bounded and the output is practically stabilized to the origin. Finally, the numerical simulation illustrates the effectiveness of the proposed scheme. © 2025 IEEE. All rights reserved.

关键词： Feedback control

来源：评论

学校读者我要写书评

暂无评论

Robust H∞ Analysis and control of Fractional-Order Systems With Ellipsoidal Parametric Uncertainty

引用

Mathematical Methods in the Applied Sciences 2025年第8期48卷 9058-9070页

作者： Zhu, Long-Jun Lu, Jun-Guo Zhu, Zhen Zhang, Qing-Hao Department of Automation Shanghai Jiao Tong University Shanghai China School of Artificial Intelligence Shanghai Normal University Tianhua College Shanghai China Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai China

In the domain of systems control, the robust control of fractional-order systems (FOSs) with ellipsoidal parameter uncertainty has received scant attention, even though ellipsoidal uncertainty is significant for quantifying and modeling parameter uncertainties. This paper addresses the gap by focusing on (Formula presented.) analysis and control of FOSs with ellipsoidal parametric uncertainty, where the fractional order is delimited to the range (Formula presented.). Two distinct categories of ellipsoidal parameter uncertainty models are considered: one corresponding to FOSs with uncertain zero positions and the other to FOSs with uncertain pole and zero positions. First, sufficient conditions for the (Formula presented.) performance analysis of FOSs with ellipsoidal parametric uncertainty are established by extending the (Formula presented.) bounded real lemma for FOSs. Next, the problems of (Formula presented.) controller synthesis are analyzed, and the state feedback (Formula presented.) controllers are designed, along with the establishment of sufficient conditions for stabilization. These conditions are given in the form of linear matrix inequalities (LMIs). Lastly, several numerical examples are provided to verify the effectiveness of the proposed results. © 2025 John Wiley & Sons Ltd.

关键词： State feedback

来源：评论

学校读者我要写书评

暂无评论

Curve-Suppression-Based Event-Triggered Mechanisms for Quasi-Synchronization of Fuzzy Delayed Neural Networks on Time Scales

引用

IEEE Transactions on Systems, Man, and Cybernetics: Systems 2025年第5期55卷 3174-3187页

作者： Wan, Peng Zhou, Yufeng Zeng, Zhigang Lai, Jingang Wuhan University of Science and Technology School of Artificial Intelligence and Automation Engineering Research Center of Metallurgical Automation and Measurement Technology Wuhan430081 China Huazhong University of Science and Technology School of Artificial Intelligence and Automation Key Laboratory of Image Processing and Intelligent control of Education Ministry of China Wuhan430074 China

The vast majority of published event-triggered mechanisms (ETMs) are constructed based on measurement errors, which introduces a problem naturally that they are updated when the measurement errors exceed the thresholds although the current obtained sampling states can make systems converge well. With this problem in mind, we redesign ETMs for quasi-synchronization of T-S fuzzy neural networks (FNNs) with time delays on time scales. First, a novel ETM is designed for continuous-time FNNs with time-varying delays to achieve quasi-synchronization, with which synchronization errors is suppressed to globally exponentially converge to a ball. Second, we introduce the ETM for continuous-time FNNs to discrete-time FNNs, owing to the existence of discrete-time states, the Lypunov function of synchronization errors run over the exponentially decay curve, but it can be suppressed to evolve under another exponentially decay curve. Third, for FNNs on time scales with constant and time-varying delays, we estimate the forward jump operator of the Lyapunov functions and design ETMs to guarantee that the Lypunov functions evolve under the exponentially decay curves, so quasi-synchronization can be achieved. Last but not least, we prove that Zeno behavior will not happen and four numerical examples are introduced to verify the validity and the superiority of the proposed ETMs in reducing information transmission. © 2013 IEEE.

关键词： Continuous time systems

来源：评论

学校读者我要写书评

暂无评论

Complementary Learning Subnetworks Towards Parameter-Efficient Class-Incremental Learning

引用

IEEE Transactions on Knowledge and Data Engineering 2025年第6期37卷 3240-3252页

作者： Li, Depeng Zeng, Zhigang Dai, Wei Suganthan, Ponnuthurai Nagaratnam Huazhong University of Science and Technology School of Artificial Intelligence and Automation Wuhan430074 China Key Laboratory of Image Processing and Intelligent Control of Education Ministry of China Wuhan430074 China China University of Mining and Technology School of Information and Control Engineering Xuzhou221116 China Qatar University Kindi Center for Computing Research College of Engineering Doha2713 Qatar

In the scenario of class-incremental learning (CIL), deep neural networks have to adapt their model parameters to non-stationary data distributions, e.g., the emergence of new classes over time. To mitigate the catastrophic forgetting phenomenon, typical CIL methods either cumulatively store exemplars of old classes for retraining model parameters from scratch or progressively expand model size as new classes arrive, which, however, compromises their practical value due to little attention paid to parameter efficiency. In this paper, we contribute a novel solution, effective control of the parameters of a well-trained model, by the synergy between two complementary learning subnetworks. Specifically, we integrate one plastic feature extractor and one analytical feed-forward classifier into a unified framework amenable to streaming data. In each CIL session, it achieves non-overwritten parameter updates in a cost-effective manner, neither revisiting old task data nor extending previously learned networks;Instead, it accommodates new tasks by attaching a tiny set of declarative parameters to its backbone, in which only one matrix per task or one vector per class is kept for knowledge retention. Experimental results on a variety of task sequences demonstrate that our method achieves competitive results against state-of-the-art CIL approaches, especially in accuracy gain, knowledge transfer, training efficiency, and task-order robustness. Furthermore, a graceful forgetting implementation on previously learned trivial tasks is empirically investigated to make its non-growing backbone (i.e., a model with limited network capacity) suffice to train on more incoming tasks. © 2025 IEEE.

关键词： Contrastive Learning

来源：评论

学校读者我要写书评

暂无评论

Semi-Autonomous Navigation Based on Local Semantic Map for Mobile Robot

引用

Journal of Shanghai Jiaotong university(Science) 2025年第1期30卷 27-33页

作者： ZHAO Yanfei XIAO Peng WANG Jingchuan GUO Rui Department of Automation Institute of Medical RoboticsShanghai Jiao Tong UniversityShanghai200240China State Key Laboratory of System Control and Information Processing Ministry of Education of ChinaShanghai200240China Shanghai Engineering Research Center of Intelligent Control and Management Shanghai200240China State Grid Intelligence Technology Co. Ltd.Jinan250013China

Mobile robots represented by smart wheelchairs can assist elderly people with mobility *** paper proposes a multi-mode semi-autonomous navigation system based on a local semantic map for mobile robots,which can assist users to implement accurate navigation(e.g.,docking)in the environment without prior *** order to overcome the problem of repeated oscillations during the docking of traditional local path planning algorithms,this paper adopts a mode-switching method and uses feedback control to perform docking when approaching semantic *** last,comparative experiments were carried out in the real *** show that our method is superior in terms of safety,comfort and docking accuracy.

关键词： semi-autonomous navigation mobile robot semantic map voice interaction

来源：评论

学校读者我要写书评

暂无评论

Event-triggered Nonlinear control with Reset Dynamics

引用

IEEE Transactions on Automatic control 2025年

作者： Zhu, Lijun Chen, Zhiyong The Ministry of Education Key Laboratory of Imaging Processing and Intelligence Control China Huazhong University of Science and Technology School of Artificial Intelligence and Automation Wuhan430074 China The University of Newcastle School of Engineering CallaghanNSW2308 Australia

In this paper, we propose an improved event-triggered control law based on Lyapunov function method for a class of nonlinear systems by integrating a monotonically decreasing dynamics with a reset mechanism at each sampling instance. It is rigorously guaranteed that the sampling interval can be increased compared to a recently designed Lyapunov-function based event-triggered control law when adopted at each step while the advantages compared with other existing event-triggered control laws are maintained. Then, the improved event-triggered law is applied in the adaptive control scheme. Finally, it is verified by numerical examples that the sampling efficiency is improved when the design parameter is appropriately chosen. © 1963-2012 IEEE.

关键词： Lyapunov functions

来源：评论

学校读者我要写书评

暂无评论

Disturbance Estimation of Legged Robots: Predefined Convergence via Dynamic Gains

arXiv

引用

arXiv 2025年

作者： Li, Bolin Cai, Peiyuan Zuo, Gewei Zhu, Lijun Ding, Han School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan430072 China Key Laboratory of Imaging Processing and Intelligence Control China State Key Laboratory of Intelligent Manufacturing Equipment and Technology Huazhong University of Science and Technology China

In this study, we address the challenge of disturbance estimation in legged robots by introducing a novel continuous-time online feedback-based disturbance observer that leverages measurable variables. The distinct feature of our observer is the integration of dynamic gains and comparison functions, which guarantees predefined convergence of the disturbance estimation error, including ultimately uniformly bounded, asymptotic, and exponential convergence, among various types. The properties of dynamic gains and the sufficient conditions for comparison functions are detailed to guide engineers in designing desired convergence behaviors. Notably, the observer functions effectively without the need for upper bound information of the disturbance or its derivative, enhancing its engineering applicability. An experimental example corroborates the theoretical advancements achieved. Copyright © 2025, The Authors. All rights reserved.

关键词： Continuous time systems

来源：评论

学校读者我要写书评

暂无评论

Game-based Secondary control for DC Microgrids with Nash Equilibrium

引用

IEEE Transactions on Energy Conversion 2025年

作者： Yuan, Qi-Fan Wang, Yan-Wu Liu, Xiao-Kang Guo, Kai-Yuan Huazhong University of Science and Technology Key Laboratory of Image Processing and Intelligent Control School of Artificial Intelligence and Automation Wuhan430074 China

Voltage regulation and current sharing are two major issues when designing distributed control strategies for DC microgrids. However, power supply economy of local generators also needs to be considered. In this paper, a game-based framework is constructed, where multiple generators are regarded as the participants with secondary control signals being the game actions. A distributed secondary control algorithm is proposed, while information mask is introduced to avoid transmitting true control signal to neighbors. Then, payoff function is designed for each generator, which is composed of voltage regulation error, current sharing error and the local generation cost. It is proved that under the proposed secondary control algorithm in conjunction with the payoff function, a unique Nash equilibrium can be reached. Consequently, the minimum of the payoff function can be achieved, where the optimization of system control behavior and local economic operation can be realized simultaneously. Numerical simulations and experimental tests are carried out to demonstrate the effectiveness of the proposed secondary control strategy within several scenarios. © 1986-2012 IEEE.

关键词： Microgrids

来源：评论

学校读者我要写书评

暂无评论

Surface-PMSM Sensorless control Strategy Based on Reduced-Order Linear Kalman Filter Cooperating with Prediction Error Rolling Compensation

引用

IEEE Transactions on Power Electronics 2025年

作者： Xu, Sang Shen, Anwen Tang, Qipeng Wang, Miaomiao Luo, Pan Luo, Xin Xu, Jinbang National Key Laboratory of Science and Technology on Multispectral Information Processing Key Laboratory of Image Processing and Intelligent Control School of Artificial Intelligence and Automation Wuhan430074 China Science and Technology on Reactor System Design Technology Laboratory Chengdu China

Kalman filter (KF) is increasingly attracted for sensorless control of surface permanent magnet synchronous motors (SPMSMs) due to its strong robustness against measurement and system noise. However, conventional method suffers from poor position and speed estimation accuracy under dynamic conditions, and high computational cost. In order to solve these problems, an enhanced sensorless control strategy based on reduced-order linear Kalman filter (RLKF) cooperating with prediction error rolling compensation is introduced in this paper. Differing from conventional method, a reduced-order linear state equation encompassing rotor position, speed and torque disturbance is constructed. Then, by obtaining the prediction error of system output using the motor current equation in the predictive reference frame, the optimal estimation of rotor position and speed in KF algorithm is achieved based on the reduced-order model. This not only simplifies the calculation process, but also enhances the position and speed estimation accuracy under dynamic conditions. Meanwhile, a prediction error rolling compensation algorithm is developed to minimize the estimation deviations caused by motor parameters variations. Additionally, the system's dynamic performance is further improved with an adopted speed controller based on torque disturbance feedforward and acceleration feedback. Finally, experimental results verify the effectiveness and feasibility of the proposed strategy.1 © 1986-2012 IEEE.

关键词： Permanent magnets

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：