检索结果-内蒙古大学图书馆

Chinese control Conference (CCC)

作者： Jiajun Chu Weihua Cao Chao Gan Yulong Yang School of Automation China University of Geosciences Wuhan P. R. China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan P. R. China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan P. R. China

Deep-sea unmanned exploration equipment is an important tool for exploring and developing the resources in the ocean, and it can survey the deep-sea environment more visually with the help of visual images. However, the complex and variable environment and the low resolution of the underwater lens lead to the poor resolution of the images acquired by the equipment. In this paper, we propose a residual-dense connected method applied to unmanned deep-sea exploration equipment to improve it's image resolution. The method uses dense connections within the residual structure to improve the model detail information acquisition to ensure accuracy and model stability of model. Secondly, through the study of the model performance, a high precision residual-dense connected model with less computational effort is designed. Finally, the model is trained and tested using environmental images in deep-sea conditions, and it is demonstrated that the method can be applied to deep-sea unmanned exploration equipment for fast, accurate, and stable image super-resolution processing.

关键词：

来源：评论

学校读者我要写书评

暂无评论

A New Total Variation Denoising Algorithm for Piecewise Constant Signals Based on Non-convex Penalty 1

引用

2nd International Conference on Neural Computing for Advanced Applications, NCAA 2021

作者： Lv, Donghao Cao, Weihua Hu, Wenkai Wu, Min School of Automation China University of Geosciences Wuhan430074 China School of Information Engineering Inner Mongolia University of Science and Technology Baotou014010 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan China

ISBN: (数字)9789811651885

ISBN: (纸本)9789811651878

Total variation signal denoising is an effective nonlinear filtering method, which is suitable for the restoration of piecewise constant signals disturbed by white Gaussian noises. Towards efficient denoising of piecewise constant signals, a new total variation denoising algorithm based on an improved non-convex penalty function is proposed in this paper. While ensuring the objective function is convex, a new non-convex penalty is designed. The denoising efficiency is improved by updating the dynamic total variational adjustment in the penalty function to the static adjustment. Experimental results demonstrated that the proposed denoising algorithm improved the denoising efficiency without affecting the denoising effect. The overall performance was shown better than the current excellent denoising algorithm. © 2021, Springer Nature Singapore Pte Ltd.

关键词： Efficiency

来源：评论

学校读者我要写书评

暂无评论

Design of intelligent monitoring and dynamic early warning system for geological hazards

Design of intelligent monitoring and dynamic early warning s...

引用

Chinese automation Congress (CAC)

作者： Ziliang Yu Weihua Cao Chao Gan School of Automation China University of Geosciences Wuhan China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan China Ministry of Education Engineering Research Center of Intelligent Technology for Geo-Exploration Wuhan China

intelligent monitoring system is crucial to the process of geological disaster prevention and control, and plays a vital role in improving prevention and control efficiency and early warning accuracy. An intelligent monitoring and dynamic early warning system for geological hazards is designed. First, four main functional requirements of data fusion and visualization, single landslide dynamic warning, regional landslide susceptibility evaluation and risk level inquiry are analyzed in detail. Then, the system network architecture is analyzed and a six-layer software framework is designed. Finally, a new online data architecture is proposed. The designed system provides a feasible solution for geological disaster prevention and control.

关键词： Geology Scalability Software algorithms Computer architecture Network architecture Alarm systems Terrain factors

来源：评论

学校读者我要写书评

暂无评论

Surface Defect Detection of Sanitary Ceramic Product Utilizing High-resolution Image on Two Different Scales

Surface Defect Detection of Sanitary Ceramic Product Utilizi...

引用

Chinese control and decision Conference, CCDC

作者： Xing-Ao Wang Jianqi An Yisheng Mei Xin Chen Min Wu School of Automation China University of Geosciences Wuhan China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan China

ISBN: (纸本)9781665478977

Surface defect detection of sanitary ceramic products is an important part of the production process. The deep learning method is the mainstream research direction in the field of defect detection. Since there are many small defects on the surface of sanitary ceramic products, it is an effective means to use a high-resolution camera to obtain images. The detection speed of high-resolution pictures and the interference of background are the difficult problems in detection. Therefore, this paper designs a two-scale detection framework to detect and locate defects of sanitary ceramics utilizing high-resolution images. The two-scale detection framework speeds up the detection of high-resolution images and weakens the interference of the background by dividing the defect detection task into two parts, a workpiece region recognition task on large scale and a defect detection task on small scale. The experiments show that the two-scale detection method has a better detection speed and accuracy rate compared with the single-scale method, which proves the superiority of the proposed method.

关键词： Deep learning Image recognition Ceramic products Interference Production Cameras Ceramics

来源：评论

学校读者我要写书评

暂无评论

Distributed Coverage control of Multi-Agent systems in Uncertain Environments using Heat Transfer Equations

arXiv

引用

arXiv 2022年

作者： Zheng, Yinan Zhai, Chao The School of Automation China University of Geosciences Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan430074 China

This paper addresses the coverage control problem of multi-agent system in the uncertain environment. With the aid of Voronoi partition, a distributed coverage control formulation of multi-agent system is proposed to complete the workload in the uncertain environments. Driven by the gradient of thermal field, each agent is able to move around for clearing the workload on its own subregion. Theoretical analysis is conducted to ensure the completion of workload in finite time. Finally, numerical simulations are carried out to demonstrate the effectiveness and advantages of the proposed coverage control approach as compared to other existing approaches. © 2022, CC BY.

关键词： Multi agent systems

来源：评论

学校读者我要写书评

暂无评论

Non-cooperative Stochastic Target Encirclement by Anti-synchronization control via Range-only Measurement

Non-cooperative Stochastic Target Encirclement by Anti-synch...

引用

IEEE International Conference on Robotics and automation (ICRA)

作者： Fen Liu Shenghai Yuan Wei Meng Rong Su Lihua Xie Guangdong Provincial Key Laboratory of Intelligent Decision and Cooperative Control School of Automation Guangdong University of Technology Guangzhou the Centre for Advanced Robotics Technology Innovation (CARTIN) School of Electrical and Electronic Engineering Nanyang Technological University Singapore Singapore

This paper investigates the stochastic moving target encirclement problem in a realistic setting. In contrast to typical assumptions in related works, the target in our work is non-cooperative and capable of escaping the circle containment by boosting its speed to maximum for a short duration. In extreme conditions, where GPS signals are not available, weight restrictions are present, and ground guidance is absent, the agents can rely solely on their onboard single-modality perception tools to measure the distances to the target. The distance measurement allows for creating a position estimator by providing a target position-dependent variable. Furthermore, the construction of the unique distributed anti-synchronization controller (DASC) can guarantee that the two agents track and encircle the target swiftly. The convergence of the estimator and controller is rigorously evaluated using the Lyapunov technique. A real-world UAV-based experiment is conducted to illustrate the performance of the proposed methodology in addition to a simulated Matlab numerical sample. Our video demonstration can be found in the URL https://***/EDVLvP-bk8M.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Emotion Recognition via Environmental Context and Human Body

Emotion Recognition via Environmental Context and Human Body

引用

Industrial Cyber-Physical systems (ICPS)

作者： Cheng-Shan Jiang Zhen-Tao Liu School of Automation China University of Geosciences Wuhan P. R. China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan P. R. China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan P. R. China

To promote the humanized interactive experience of the intelligent device and system, emotional intelligence has become a popular research field in the human-machine interaction. The previous research on emotion recognition based on computer vision has mostly been carried out by analysing facial expression or body posture, and psychological studies show that scene context also contributes some important information on emotion recognition. In addition, most context-aware emotion recognition studies focus on exploring the relevance analysis of environmental semantics, but the influence of feature encoder on semantic information embedding has not been fully discussed. In this paper, we proposed a Global Semantic Feature Enhancement-Dual Stream Densely Connected Network (GSFE-DSDCN) to enhance global semantic information learning from the perspectives of dimension and spatial. Densely connected pattern is introduced to concatenate the shallow and deep layers output, which fuses the semantic information of low-dimensional geometric features and high-dimensional abstract context features together. The Global Multi-Scale Feature Recalibration (GMSFR) module expands the receptive field in spatial, which effectively improves the global semantic features extraction capability of feature encoder. We evaluate the proposed method on the EMOTIC data set, and experimental results are shown to be competitive with the state-of-the-art algorithms.

关键词： Human computer interaction Emotion recognition Computer vision Fuses Biological system modeling Semantics Psychology

来源：评论

学校读者我要写书评

暂无评论

An Integrated intelligent Autonomous Driving Bulldozer System: Pose Estimation, Object Detection, and Work Planning for Dumping Operations

引用

Journal of Field Robotics 2025年第0期

作者： Peng, Gang Gao, Qiang Liu, Xingyu Zhou, Yicheng Duan, Hangqi Wu, ZhanGang Hu, Bin Zhu, Xukang Xu, Daosheng School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan China Key Laboratory of Image Processing and Intelligent Control Ministry of Education Wuhan China Engineering Research Center of Autonomous Intelligent Unmanned Systems Ministry of Education Wuhan China Shantui Construction Machinery Co. Ltd. Jining China

In recent years, the rapid advancement of automation control and intelligent sensing technologies has positioned autonomous driving as a focal point of interest for both academia and industry. As core equipment in modern construction and industrial production, engineering machinery urgently requires intelligent transformation. To promote the intelligent development of engineering machinery, we have designed an integrated intelligent autonomous driving bulldozer system, which can be extended to various types of engineering machinery. For the specific mine dumping operation environment, we propose a multisensor fusion pose estimation algorithm framework based on the Global Navigation Satellite System, inertial measurement unit, visual cameras, and light detection and ranging (LiDAR) to address issues arising from sensor failures under harsh construction conditions. Furthermore, to ensure safety during task execution, we design a three-dimensional object detection method based on the optimal observation plane from LiDAR data. By integrating pose estimation and environmental perception results, we develop a comprehensive work planning and path-tracking algorithm to maintain task efficiency. Experimental results demonstrate that our intelligent autonomous driving bulldozer system performs excellently under various working conditions. The accuracy of its pose estimation, object detection, and path tracking meets the requirements of actual construction environments, showcasing its significant potential in engineering applications. © 2025 Wiley Periodicals LLC.

关键词： Construction equipment

来源：评论

学校读者我要写书评

暂无评论

An Enhanced Fuzzy Repetitive-control Design and Optimisation Method based on 2D Performance Index 10

An Enhanced Fuzzy Repetitive-Control Design and Optimisation...

引用

10th IEEE Data Driven control and Learning systems Conference, DDCLS 2021

作者： Zhang, Manli Wu, Min Tian, Shengnan She, Jinhua School of Automation China University of Geosciences Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan430074 China School of Engineering Tokyo University of Technology Hachioji192-0982 Japan

ISBN: (纸本)9781665424233

This paper concerns the design and optimisation of two-dimensional (2D) repetitive control of nonlinear systems based on the Takagi-Sugeno (T-S) fuzzy model. First, a continuous-discrete 2D model of nonlinear repetitive-control systems based on T-S fuzzy model is constructed by utilizing the 2D characteristics of continuous control and discrete learning actions in the repetitive-control process. Next, a fuzzy Lyapunov-Krasovskii functional derives the linear-matrix-inequality-based stability condition with a low conservatism. Two positive and two nonzero parameters in the fuzzy Lyapunov-Krasovskii functional tune the control and learning actions. Then the particle swarm optimisation algorithm based on a 2D performance index searches for the best parameter combination, resulting in the optimal 2D controller gains. A numerical example is given to demonstrate the effectiveness of the method. © 2021 IEEE.

关键词： Linear matrix inequalities

来源：评论

学校读者我要写书评

暂无评论

Exponential Stability Analysis for Delayed Neural Networks via A Cubic Function Negative-Determination Lemma

Exponential Stability Analysis for Delayed Neural Networks v...

引用

Chinese control Conference (CCC)

作者： Wen-Xuan Zhao Yun-Fan Liu Yu-Long Fan Chuan-Ke Zhang School of Automation China University of Geosciences Wuhan P. R. China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan P. R. China Ministry of Education Engineering Research Center of Intelligent Technology for Geo-Exploration Wuhan P. R. China

This paper concerns with the exponential stability of delayed neural networks via Lyapunov-Krasovskii functional (LKF) method. Initially, an improved augmented delay-product-type LKF containing an additional double integral state is established, which introduces more delayed states and has less conservatism. In the LKF's derivative, the function has high order of delay due to the existence of exponent. Thus, in order to obtain tractable linear matrix inequalities, three state vectors are used to reduce the order of the function to cubic. Secondly, to achieve the negative-definiteness requirement, a negative-determination lemma for cubic functions with less conservatism is employed. Then, a less conservative delay-dependent stability criterion for neural networks with time-varying delays is established. Finally, the validity of the proposed delay-dependent stability criterion is illustrated by two numerical examples.

关键词：

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：