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Super-resolution reconstruction method of face image based on attention mechanism

IEEE Access 2021年

作者： Yu, Chenglin Pei, Hailong Key Laboratory of Autonomous Systems and Networked Control Ministry of EducationUnmanned Aerial Vehicle Systems Engineering Technology Research Center of GuangdongSchool of Automation Scinece and EngineeringSouth China University of TechnologyGuangzhou510640China.

In recent years, convolutional neural network in Single image super-resolution field show good results. Deep networks can establish complex mapping between low-resolution and high-resolution images, making the reconstructed images quality a great progress over traditional methods. In order to be able to generate face images with rich texture details, the algorithm proposed in this paper captures implicit weight information in channel and space domains through dual attention modules, so as to allocate computing resources more effectively and speed up the network convergence. Fusion of global features through residual connections in this network not only focus on learning the high frequency information of images that has been lost, but also accelerate the network convergence through effective feature supervision. In order to alleviate the defects of MAE loss function, a special Huber loss function is introduced in the algorithm. The experimental results on benchmark show that the proposed algorithm has a significant improvement in image reconstruction accuracy compared with existed SISR methods. CCBY

关键词： Convolution

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An Improved Chimp Optimization Algorithm for Short-term Hydrothermal Scheduling

IAENG International Journal of Computer Science

引用

IAENG International Journal of Computer Science 2022年第3期49卷

作者： Chen, Gonggui Wang, Shumin He, Yongsheng Shang, Wanfeng Long, Hongyu Key Laboratory of Industrial Internet of Things and Networked Control Ministry of Education Chongqing University of Posts and Telecommunications Chongqing400065 China Chongqing University of Posts and Telecommunications Chongqing400065 China State Grid Chongqing Electric Power Company Chongqing400015 China Guangdong Provincial Key Lab of Robotics and Intelligent System Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Shenzhen Shenzhen518055 China Chongqing Key Laboratory of Complex Systems and Bionic Control Chongqing University of Posts and Telecommunications Chongqing400065 China

The short-term hydrothermal scheduling (STHS) is a complex non-linear, non-convex and high-dimensional mathematical optimization problem. Due to the fact that the original chimp optimization algorithm (ChOA) is likely to fall into local optimum and has the disadvantage of low population diversity, an improved chimp optimization algorithm (IChOA) is proposed to solve the STHS problem. Firstly, Logistic-Tent chaotic mapping is employed to initialize the population and increase the population diversity. Then a new nonlinear convergence factor is introduced to make the optimization search process more applicable to STHS problems. Next, particle swarm algorithm (PSO) and gravitational search algorithm (GSA) are combined to enhance the shortcoming and balance the global search ability and local exploration ability of ChOA. Moreover, Cauchy mutation and opposition-based learning strategy are supplemented as perturbation interference when the optimal position is not updated to improve the ability to leap out of the local optimum. Finally, a graded optimization strategy is adopted for the constraint handing of dynamic reservoir balance and thermal power balance. Three standard hydrothermal power systems are utilized to verify the practicability and validity of the proposed method. Results of simulations reveal that IChOA has significant competitive advantages in addressing the STHS problem. © 2022, IAENG International Journal of Computer Science. All Rights Reserved.

关键词： Particle swarm optimization (PSO)

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A Novel Fractional-Order Model of Medium-Frequency Respiratory Impedance

A Novel Fractional-Order Model of Medium-Frequency Respirato...

引用

International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI)

作者： Hongwei Wang Bin Li Hongqiang Mo Yuanda Xu Zhaoxiang Xu Yanqing Xie School of Automation Science and Engineering South China University of Technology Guangzhou P.R. China Key Laboratory of Autonomous Systems and Networked Control Ministry of Education South China University of Technology Guangzhou P.R. China Department of Critical Care Medicine The First Affiliated Hospital Guangzhou Medical University Guangzhou P.R. China The First Affiliated Hospital Guangzhou Medical University Guangzhou P.R. China

ISBN: (数字)9798331507398

ISBN: (纸本)9798331507404

Respiratory impedance in the medium-frequency range reflects the dynamic properties of airways and lung tissues, and plays an important role in the early diagnosis of pulmonary diseases. Fractional-order models can characterize complex dynamics with fewer parameters compared to integer-order models, and have been used to represent the medium-frequency characteristics of the respiratory impedance. There have been multiple fractional-order models, but there is no consensus on which model is most reasonable. This paper proposes a novel fractional-order model, which consists of a viscous resistance, an inertia resistance, and an elastic resistance. Unlike existing models, in the proposed model, the inertial resistance is represent with a fractional-order term, while the other two resistances are represent with integer-order terms. The proposed model was employed to represent the medium-frequency respiratory impedance determined by appling impulse oscillometry to 8 healthy subjects. The results in terms of fitting error and determination coefficient indicate that the proposed model fits the data well. Furthermore, when examining the variation of the parameters of the model over time, the results indicate that the parameters are highly correlated with tidal volume. However, the parameters of other existing fractional-order models did not exhibit this correlation.

关键词： Resistance Solid modeling Correlation Fluctuations Atmospheric modeling Pulmonary diseases Lungs Fitting Signal processing Impedance

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Combining Transformer and Convolutional Neural Network for Smoke Detection 9th

Combining Transformer and Convolutional Neural Network for...

引用

9th International Forum on Digital Multimedia Communication, IFTC 2022

作者： Gong, Yafei Lian, Xinkang Ma, Xuanchao Xia, Zhifang Zhou, Chengxu Faculty of Information Technology Beijing University of Technology Beijing China Engineering Research Center of Intelligent Perception and Autonomous Control Ministry of Education Beijing China Beijing Laboratory of Smart Environmental Protection Beijing China Beijing Key Laboratory of Computational Intelligence and Intelligent System Beijing China Beijing Artificial Intelligence Institute Beijing China National Information Center Beijing China School of Electronic and Information Engineering Liaoning University of Technology Liaoning Jinzhou China Key Laboratory of Intelligent Control and Optimization for Industrial Equipment of Ministry of Education Dalian University of Technology Dalian China

ISBN: (纸本)9789819908554

Smoke detection plays a crucial role in the safety production of petrochemical enterprises and fire prevention. Image-based machine learning and deep learning methods have been widely studied. Recently, many works have applied the transformer to solve problems faced by computer vision tasks (such as classification and object detection). To our knowledge, there are few studies using the transformer structure to detect smoke. In order to research the application potential and improve the performance of the transformer in the smoke detection field, we propose a model consisting of two transformer encoders and a convolutional neural network (CNN) module. The first transformer encoder can be used to establish the global relationship of an image, and the CNN structure can provide additional local information to the transformer. The fusion of global information and local information is conducive to the second transfer encoder to make better decisions. Experiments results on large-size dataset for industrial smoke detection illustrate the effectiveness of the proposed model. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Smoke

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A method of laser focusing control in microlaser-induced breakdown spectroscopy

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Plasma Science and Technology 2019年第3期21卷 31-39页

作者： Wei WANG Lanxiang SUN Peng ZHANG Liming ZHENG Lifeng QI Wei DONG Shenyang Institute of Automation Chinese Academy of Sciences Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences University of Chinese Academy of Sciences Key Laboratory of Networked Control System Chinese Academy of Sciences

This paper presents a method for the automatic adjustment of the laser defocusing amount in micro-laser-induced breakdown spectroscopy. A microscopic optical imaging system consisting of a CCD camera and a 20× objective lens was adopted to realize the method. The real-time auto-focusing of the system was achieved by detecting the effective pixels of the light spot generated by the laser pointer. The focusing accuracy of the method could achieve 3 μm. The element concentrations of Mn and Ni in low-alloy steels were analyzed at a crater diameter of about 35 μm using the presented method. After using the presented method, the determination coefficients of Mn and Ni both exceeded 0.997, with the root-mean-square errors being 0.0133 and 0.0395, respectively. Scanning analysis was performed on the inclined plane and the curved surface by means of focusing control and non-focusing control. Ten characteristic spectral lines of Fe were selected as the analysis lines. With the focusing control, the average relative standard deviations obtained on the inclined plane and curved surface were both less than 5%, and much less than the values without focusing control, 14.6% and 40.39%.

关键词： LIBS microanalysis ablation crater focusing control

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Prescriptive Manufacturing in Society 5.0: Human autonomous Organizations and “On-Demand” Smart Services

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IFAC-PapersOnLine 2024年第3期58卷 139-144页

作者： Xiao Wang Jun Huang Jing Yang Xiaoxing Wang Fei-Yue Wang Engineering Research Center of Autonomous Unmanned System Technology Ministry of Education Anhui University Hefei 230601 China Macau University of Science and Technology Macau 999078 China School of artificial Intelligence University of Chinese Academy of Sciences Beijing 100049 China Beijing SANBODY Technology Company Ltd Beijing 214000 China Qingdao Academy of Intelligent Industries Qingdao 266109 China State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing 100190 China

Society 5.0 addresses human behaviors and their consequences in social management, while emphasizing the integration of Cyber-Physical-Social Spaces to achieve a highly connected and circulated society. Prompted by the various social needs expressed on social media platforms, Prescriptive Manufacturing (PM) emerges as a proactive pre-manufacturing paradigm. This paper delves into PM within the context of Society 5.0. It highlights the development of Human autonomous Organizations (HAOs) and the delivery of “on-demand” smart services, which are customized to meet both individual and broader societal demands. The social sensing framework of social needs across different social media platforms that enables the identification and anticipation of consumer demands in real-time is illustrated. This data-driven insight leverages artificial intelligence and robotics to facilitate customized design and on-demand production, aligning product creation with real user requirements. Furthermore, we discuss the implementation of human-centered smart services in PM, such as virtual try-on, virtual fitting, personalized retrofit, user-friendly scheduling, and proximity logistics, which not only enhance consumer experience but also optimize resource efficiency By examining the symbiosis between technological advancements and social need fulfillment, this study sheds light on how PM and HAOs can foster a more responsive, sustainable, and inclusive economy in society, ultimately contributing to a higher quality of life and sustainable development goals of Society 5.0.

关键词： Social Needs Sensing Human autonomous Organization Customized Design personalized fine-tuning prescriptive manufacturing Human-Centric Smart Services

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Observer-based Dynamic Surface control for Robotic Manipulator with Fixed-time Convergence 7

Observer-based Dynamic Surface Control for Robotic Manipulat...

引用

7th International Conference on Information, Cybernetics, and Computational Social systems, ICCSS 2020

作者： Zhu, Chengzhi Zuo, Lei Wang, Ning Key Laboratory of Autonomous Systems and Networked Control College of Automation Science and Engineering South China University of Technology Guangzhou510640 China School of Electronic and Control Engineering Chang'an University Xi'an710064 China School of Information Engineering Chang'an University Xi'an710064 China

ISBN: (纸本)9781728162461

A state feedback dynamic surface tracking control algorithm is proposed for parametric linearized manipulator model in this paper. Different from ordinary finite-time control schemes, fixed-time convergence can be achieved in the proposed algorithm via both of high and low-degree terms in the controller such that the settling time can be preestablished by the designed parameters independent of the system initial conditions. Moreover, the problem of the 'explosion of complexity' and the singularity can be avoided by constructing an auxiliary controller with a first-order filter. The semi-global fixed-time uniform convergence of all the signals in the closed-loop system can be proved by Lyapunov theorem. In order to avoid the employment of acceleration signals and obtain better tracking performance during the procedure, a kind of observer based on uniform exact differentiators was used to compensate the uncertainties online. Finally the superiority of the proposed method has been verified by simulations based on a 2-DOF robot manipulator. © 2020 IEEE.

关键词： State feedback

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Initialization-Free Distributed Constrained Optimization Algorithms with a Pre-Specified Time

Initialization-Free Distributed Constrained Optimization Alg...

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IEEE Conference on Decision and control

作者： Xiasheng Shi Chaoxu Mu Changyin Sun Lu Ren Yanxu Su School of Artificial Intelligence Anhui University Hefei China Ministry of Education Engineering Research Center of Autonomous Unmanned System Technology Anhui University Hefei China Anhui Provincial Engineering Research Center for Unmanned System and Intelligent Technology Anhui University Heifei China Key Laboratory of Intelligent Control and Optimization for Industrial Equipment Ministry of Education Dalian University of Technology School of Electrical and Information Engineering Tianjin University Tianjin China

The distributed constrained optimization problem over an undirected communication topology is investigated in this study. It focuses on addressing a global coupled equality constraint that applies to all agents. To tackle this problem, a distributed approach with arbitrary initialization is developed by virtue of the aperiodic sampling control idea and the consensus-based multi-agent system(MAS) technology. This approach is developed to address constrained optimization problems within a pre-specified time. In addition, this predefined time is freely defined by users and irrelevant to the initial states, control coefficients, and network structure of systems. The Lyapunov stability theory completes the convergence proof of the developed method. Then, the developed method is extended to handle distributed nonlinear constrained optimization problems. Finally, The availability of two developed methods is demonstrated through two simulation examples.

关键词：

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One-Dimensional EEG Artifact Removal Network Based on Convolutional Neural Networks

Journal of Network Intelligence

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Journal of Network Intelligence 2024年第1期9卷 142-159页

作者： Xiong, Jun Meng, Xiang-Long Chen, Zhao-Qi Wang, Chuan-Sheng Zhang, Fu-Quan Grau, Antoni Chen, Yang Huang, Jing-Wei School of Computer and Data Science Minjiang University Fuzhou University Town No. 200 Xiyuangong Road Fuzhou China College of Electronic Engineering Shandong University of Science and Technology No. 579 Qianwangang Road Huangdao District Qingdao China College of Computer and Big Data Fuzhou University Fuzhou University Town No. 2 Wulongjiang North Road Fuzhou China Department of Automatic Control Technical Polytechnic University of Catalonia Autonomous Region of Catalonia Barcelona Spain Digital Media Art Key Laboratory of Sichuan Province Sichuan Conservatory of Music Fuzhou Technology Innovation Center of intelligent Manufacturing information System Minjiang University Fuzhou University Town No. 200 Xiyuangong Road Fuzhou China Fujian Province University No. 1 Campus New Village Longjiang Street Fuqing China School of Mechanical and Automotive Engineering Fujian University of Technology No. 33 Xuefu South Road University New District Fuzhou China

The electroencephalogram (EEG) serves as a significant tool in the realms of clinical medicine, cerebral investigation, and neurological disorders research. However, the EEG records we obtain are often easily contaminated by various artifacts, which can blur or distort the underlying EEG signals and make data interpretation difficult. Generally speaking, removing EEG artifacts is considered an essential step in brain signal analysis. Therefore, removing artifacts is crucial for obtaining accurate and reliable EEG signals for subsequent analysis. Recently, deep learning techniques have found widespread application across various domains for denoising tasks, including image denoising and EEG denoising. Many advanced algorithms have been developed in image denoising, which has achieved good results in enhancing low-quality images. Moreover, it has shown superior performance in EEG denoising. In contrast, few people have devoted themselves to studying EEG denoising, and existing convolutional neural network EEG denoising methods still have problems of overfitting and poor denoising effect in Electromyograph(EMG) and ElectroOculoGram(EOG) artifact removal. Therefore, this paper proposes a method called DWINet (De-artifacting with Image-based Network for EEG Signals) based on an image dehazing network DRHNet for removing artifacts from EEG signals. Specifically, our approach DWINet, addresses the de-artifacting issue in EEG signals by converting it as an image dehazing problem and utilizes the image dehazing capability of DRHNet to enhance the denoising performance of EEG signals. Experimental results demonstrate that the proposed method outperforms the compared algorithms in removing the ocular artifact in EEG signals and exhibits higher accuracy and robustness. © 2024, J. Network Intell. All rights reserved.

关键词： Image enhancement

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Hybrid Beamforming Design for Millimeter Wave Multiuser MIMO systems with Dynamic Subarrays

arXiv

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arXiv 2022年

作者： Wang, Gengshan Yang, Zhijia Gong, Tierui State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Shenyang110016 China The Key Laboratory of Networked Control System Shenyang Institute of Automation Chinese Academy of Sciences Shenyang110016 China The Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang110169 China The University of Chinese Academy of Sciences Beijing100049 China Singapore University of Technology and Design Singapore

In this letter, we investigate the millimeter wave (mmWave) downlink multiuser multiple-input multiple-output (MU-MIMO) system, adopting the dynamic subarray architecture at the base station and considering the multi-stream communication for each user. Aiming at maximizing the system spectral efficiency, we propose a novel hybrid beamforming design. First, assuming no inter-user interference (IUI), we easily get the optimal fully-digital beamformers and combiners using the singular value decomposition of each user channel and the waterfilling algorithm. Then, based on the obtained fully-digital beamformers, we propose a Kuhn-Munkres algorithm-assisted dynamic hybrid beamforming design, which guarantees that each radio-frequency chain is connected to at least one antenna. Finally, we propose to further project each obtained digital beamformer onto the null space of all the other equivalent user channels to cancel the IUI. Numerical results verify the superiority of our proposed hybrid beamforming design. © 2022, CC BY.

关键词： Millimeter waves

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