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31st British Machine Vision Conference, BMVC 2020

作者： Mustaniemi, Janne Kannala, Juho Matas, Jiri Särkkä, Simo Heikkilä, Janne Center for Machine Vision and Signal Analysis University of Oulu Finland Department of Computer Science Aalto University Finland Center for Machine Perception Faculty of Electrical Engineering Czech Technical University Prague Czech Republic Department of Electrical Engineering and Automation Aalto University Finland

The paper addresses the problem of acquiring high-quality photographs with handheld smartphone cameras in low-light imaging conditions. We propose an approach based on capturing pairs of short and long exposure images in rapid succession and fusing them into a single high-quality photograph. Unlike existing methods, we take advantage of both images simultaneously and perform a joint denoising and deblurring using a convolutional neural network. A novel approach is introduced to generate realistic short-long exposure image pairs. The method produces good images in extremely challenging conditions and outperforms existing denoising and deblurring methods. It also enables exposure fusion in the presence of motion blur. © 2020. The copyright of this document resides with its authors. It may be distributed unchanged freely in print or electronic forms.

关键词： Image enhancement

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NTIRE 2023 Challenge on Image Super-Resolution (×4): Methods and Results

NTIRE 2023 Challenge on Image Super-Resolution (×4): Method...

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2023 IEEE/CVF Conference on computer Vision and Pattern Recognition Workshops, CVPRW 2023

作者： Zhang, Yulun Zhang, Kai Chen, Zheng Li, Yawei Timofte, Radu Zhang, Junpei Zhang, Kexin Peng, Rui Ma, Yanbiao Jiao, Licheng Huang, Huaibo Zhou, Xiaoqiang Ai, Yuang He, Ran Qiu, Yajun Zhu, Qiang Li, Pengfei Li, Qianhui Zhu, Shuyuan Zhang, Dafeng Li, Jia Wang, Fan Li, Chunmiao Kim, TaeHyung Kil, Jungkeong Kim, Eon Yu, Yeonseung Lee, Beomyeol Lee, Subin Lim, Seokjae Chae, Somi Choi, Heungjun Huang, ZhiKai Chen, YiChung Chiang, YuanChun Yang, HaoHsiang Chen, WeiTing Chang, HuaEn Chen, I-Hsiang Hsieh, ChiaHsuan Kuo, SyYen Choi, Ui-Jin Conde, Marcos V. Khowaja, Sunder Ali Yoon, Jiseok Lee, Ik Hyun Gendy, Garas Sabor, Nabil Hou, Jingchao He, Guanghui Zhang, Zhao Li, Baiang Zheng, Huan Zhao, Suiyi Gao, Yangcheng Wei, Yanyan Ren, Jiahuan Wei, Jiayu Li, Yanfeng Sun, Jia Cheng, Zhanyi Li, Zhiyuan Yao, Xu Wang, Xinyi Li, Danxu Cui, Xuan Cao, Jun Li, Cheng Zheng, Jianbin Sarvaiya, Anjali Prajapati, Kalpesh Patra, Ratnadeep Barik, Pragnesh Rathod, Chaitanya Upla, Kishor Raja, Kiran Ramachandra, Raghavendra Busch, Christoph Computer Vision Lab Eth Zurich Switzerland Shanghai Jiao Tong University China University of Würzburg Germany Xidian University China Mais&cripac Institute of Automation Chinese Academy of Sciences China School of Artificial Intelligence University of Chinese Academy of Sciences China University of Science and Technology of China China Beijing Institute of Technology China School of Information Science and Technology ShanghaiTech University China School of Information and Communication Engineering University of Electronic Science and Technology of China China China Lotte Data Communication Company Seoul Korea Republic of Graduate Institute of Electronics Engineering National Taiwan University Taiwan Department of Electrical Engineering National Taiwan University Taiwan Graduate Institute of Communication Engineering National Taiwan University Taiwan ServiceNow United States MegaStudyEdu Korea Republic of Computer Vision Lab Caidas University of Würzburg Germany University of Sindh Pakistan Iklab Inc. Tech University of Korea Siheung-Si Korea Republic of Micro-Nano Electronics Department Shanghai Jiao Tong University China Electrical Engineering Department Faculty of Engineering Assiut University Egypt Hefei University of Technology China Beijing Jiaotong University China South China University of Technology Guangdong Guangzhou China Sardar Vallabhbhai National Institute of Technology India Norwegian University of Science and Technology Norway

ISBN: (纸本)9798350302493

This paper reviews the NTIRE 2023 challenge on image super-resolution (×4), focusing on the proposed solutions and results. The task of image super-resolution (SR) is to generate a high-resolution (HR) output from a corresponding low-resolution (LR) input by leveraging prior information from paired LR-HR images. The aim of the challenge is to obtain a network design/solution capable to produce high-quality results with the best performance (e.g., PSNR). We want to explore how high performance we can achieve regardless of computational cost (e.g., model size and FLOPs) and data. The track of the challenge was to measure the restored HR images with the ground truth HR images on DIV2K testing dataset. The ranking of the teams is determined directly by the PSNR value. The challenge has attracted 192 registered participants, where 15 teams made valid submissions. They achieve state-of-the-art performance in single image super-resolution. © 2023 IEEE.

关键词： Statistical tests

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Integration of ANN for Accurate Estimation and Control in Wastewater Treatment

Integration of ANN for Accurate Estimation and Control in Wa...

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International Conference on Emerging Technologies and Factory automation (ETFA)

作者： Andreea Elena Țîru Iulian Vasiliev Larisa Diaconu Ramon Vilanova Daniel Voipan Harsha Ratnaweera Department of Automatic Control and Electrical Engineering "Dunărea de Jos" University of Galaţi Galaţi Romania Department of Automation Systems and Advanced Control Research Autonomous University of Barcelona Barcelona Spain Department of Computer Science and Information Technology "Dunărea de Jos" University of Galaţi Galaţi Romania Faculty of Science and Technology (Realtek) Norwegian University of Life Sciences Ås Norway

The management of wastewater is a significant global concern that calls for innovative solutions to lessen its negative effects on the environment. Conventional techniques of treating wastewater need improvement in order to deal with newly discovered contaminants, which highlights the importance of providing precise estimates of process performance and resource requirements. The worsening water shortage situation requires a paradigm shift in which wastewater is viewed as a useful resource. It is possible to create an economy that is both sustainable and circular by treating and recycling wastewater, putting less pressure on freshwater supplies, and leaving as little of an environmental footprint as possible. This study investigates the use of Artificial Neural Networks (ANNs) as software estimators in the treatment of wastewater, with a particular emphasis on predicting ammonium concentrations in effluent. In order to deal with imbalanced time-series data, the research introduces innovative data pretreatment strategies. These techniques include a Sliding Window protocol, Data Normalization, and a K-Fold training scheme. This illustrates the potential of ANNs to revolutionize wastewater treatment procedures and drive developments in this field. The suggested method demonstrates higher performance when estimating pollutant concentrations, showing the ability of ANNs to do so.

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Distributed formation control for manipulator end-effectors

arXiv

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arXiv 2021年

作者： Wu, Haiwen Jayawardhana, Bayu De Marina, Hector Garcia Xu, Dabo Engineering and Technology Institute Groningen Faculty of Science and Engineering University of Groningen Groningen9747 AG Netherlands Department of Computer Architecture and Automatic Control Faculty of Physics Universidad Complutense de Madrid Madrid28040 Spain School of Automation Nanjing University of Science and Technology Nanjing210094 China

We present three classes of distributed formation controllers for achieving and maintaining the 2D/3D formation shape of manipulator end-effectors to cope with different scenarios due to availability of modeling parameters. We firstly present a distributed formation controller for manipulators whose system parameters are perfectly known. The formation control objective is achieved by assigning virtual springs between end-effectors and by adding damping terms at joints, which provides a clear physical interpretation of the proposed solution. Subsequently, we extend it to the case where manipulator kinematic and system parameters are not exactly known. An extra integrator and an adaptive estimator are introduced for gravitational compensation and stabilization, respectively. Simulation results with planar manipulators and with seven degree-of-freedom humanoid manipulator arms are presented to illustrate the effectiveness of the proposed approach. Copyright © 2021, The Authors. All rights reserved.

关键词： Manipulators

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Extension of Maxwell's equations for non-stationary magnetic fluids using gauss's divergence theorem

Results in Engineering

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Results in engineering 2025年 26卷

作者： Bouzidi, Mohammed NASRI, Abdelfatah Rahmoune, Mohamed Ben Hafsi, Oussama Aeggegn, Dessalegn Bitew Ghoneim, Sherif S. M. Ali, Enas Ghaly, Ramy N. R. Department of Sciences and Technology University of Tamanghasset Sersouf P.O. Box 10034 Tamanghasset11001 Algeria Energy and Materials Laboratory University of Tamanghasset Sersouf P.O. Box 10034 Tamanghasset11001 Algeria Laboratory Smart Grid and Renewable Energy SGRE University Tahri Mohamed Bechar Algeria Algeria Applied Automation and Industrial Diagnostics Laboratory Faculty of Science and Technology University of Djelfa DZ 17000 Algeria DDI Laboratory Ahmed Draia University Adrar01000 Algeria Department of Electrical and Computer Engineering Debre Markos University Debre Markos269 Ethiopia Department of Electrical Engineering College of Engineering Taif University Taif21944 Saudi Arabia University Centre for Research and Development Chandigarh University Punjab Mohali140413 India Faculty of Engineering and Technology Future University in Egypt New Cairo11835 Egypt Ministry of Higher Education & Scientific Research Industrial Technical Institute-Mataria Technical College Cairo11718 Egypt Centre for Research Impact & Outcome Chitkara University Institute of Engineering and Technology Chitkara University Punjab Rajpura140401 India

The work presented in this paper focuses on formulating the development of time-dependent electromagnetic field laws through the application of Gauss's divergence theorem. The first part of the discussion looks at the basic ideas of electromagnetism. It focuses on how classical formulations of the laws of electromagnetism can be adapted to account for non-stationary conditions, especially regarding magnetic fluids that don't conduct electricity. It is suggested that employing Gauss's divergence theorem could help improve the computational analysis of these generalized equations, which would make them more useful in magnetic fluid dynamics. The paper examines the intricate interactions between non-conductive particles and conductive fluids under magnetic fields. By putting these interactions into a single theoretical framework, this work aims to help us understand non-stationary electromagnetic phenomena and how they affect many different scientific and engineering fields. The concluding section of the study examines the prospective practical applications of these extended equations. They could enable the development of more advanced electromagnetic devices and systems. Creating a strong set of analytical tools that can find new scientific paths and useful applications is the main goal of the study, particularly in the areas of electromagnetic induction and fluid dynamics. This research offers potential for substantial progress in both theoretical comprehension and technological advancement, The proposed method is applicable to real-world systems such as ferrofluid-based cooling, magnetic dampers, plasma generators, and smart electromagnetic devices. These applications demonstrate the practical benefits of coupling field behavior with boundary dynamics using Gauss's theorem. © 2025

关键词： Electromagnetic induction

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Design and Implementation of Neuro-Fuzzy Control Approach for Robot's Trajectory Tracking

Design and Implementation of Neuro-Fuzzy Control Approach fo...

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International conference of Electronics, Communication and Aerospace Technology (ICECA)

作者： Kiruba Sandou D Sunad kumara A N Binod Kumar Choudhary Shashikala Gurpur Sarishma Natrayan L M. SivaramKumar Department of Robotics and Automation Manakula Vinayagar Institute of Technology Pondicherry India Department of Computer Science and Engineering BGS Institute of Technology Adichunchanagiri University Mandya Karnataka India Department of Electrical and Electronics Engineering ARKA Jain University Jamshedpur Jharkhand India Faculty of Law Symbiosis Law School (SLS) Symbiosis International (Deemed University) (SIU) Pune Maharashtra India Department of Management Studies Graphic Era Deemed to be University Dehradun Uttarakhand India Department of Mechanical Engineering Saveetha School of Engineering SIMATS Chennai Tamilnadu India Department of EEE Karpagam Academy of higher education Coimbatore Tamiinadu

Achieving precise trajectory tracking while minimizing errors, reducing settling time, and curbing overshoot presents a significant challenge in the domain of robot-manipulator control. In response, this paper proposes a novel controller design for robot manipulators, incorporating two distinct approaches: a conventional fuzzy controller and an advanced Neuro-Fuzzy controller. These controllers are tailored to elevate trajectory tracking performance by simultaneously optimizing time characteristics in robot manipulator responses. To assess their efficacy, a range of test scenarios is devised, encompassing different trajectory types, including linear and nonlinear paths. Upon comparative analysis, the results highlight an intriguing contrast: while the fuzzy controller exhibits higher maximum overshoot and longer settling times in the robot's response, the Neuro-Fuzzy controller consistently demonstrates superior performance. The comprehensive error analysis such as Integral Square Error (ISE) and Integral Absolute Error (IAE) further underscores the capability of the Neuro-Fuzzy-based robot manipulator in delivering trajectory tracking precision. This study contributes to the advancement of trajectory control techniques for robot manipulators, paving the way for enhanced automation and performance across various applications.

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Distributed formation control of manipulators' end-effector with internal model-based disturbance rejection

arXiv

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arXiv 2021年

作者： Wu, Haiwen Jayawardhana, Bayu de Marina, Hector Garcia Xu, Dabo Engineering and Technology Institute Groningen Faculty of Science and Engineering University of Groningen Groningen9747 AG Netherlands Department of Computer Architecture and Automatic Control Faculty of Physics Universidad Complutense de Madrid Madrid28040 Spain The School of Automation Nanjing University of Science and Technology Nanjing210094 China

This paper addresses the problem of end-effector formation control for manipulators that are subjected to external disturbances: input disturbance torques and disturbance forces at each end-effector. The disturbances are assumed to be non-vanishing and are superposition of finite number of sinusoidal and step signals. The formation control objective is achieved by assigning virtual springs between end-effectors, by adding damping terms at joints, and by incorporating internal model-based dynamic compensators to counteract the effect of the disturbances;all of which presents a clear physical interpretation of the proposed approach. Simulation results are presented to illustrate the effectiveness of the proposed approach. © 2021, CC BY.

关键词： End effectors

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The Monitoring System of Aquaculture Environment

The Monitoring System of Aquaculture Environment

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International Symposium on Computational Intelligence and Design, ISCID

作者： Chunxia JIN Qiuchan BAI Faculty of Computer & Software Engineering Huaiyin Institute of Technology Huaian China Faculty of Automation Huaiyin Institute of Technology Huaian China

ISBN: (数字)9781728184463

ISBN: (纸本)9781728184470

According to the needs of the aquaculture industry, this article proposes to design an aquaculture environment monitoring system for collecting temperature, PH, and dissolved oxygen parameters that affect fishery water quality environment, real-time tracking and monitoring, remote transmission and abnormal handling, etc. The system has played an important role in the application of fish breeding industry, providing technical support for the development of the breeding industry, and bringing greater economic profits to farmers.

关键词： Aquaculture Monitoring Temperature sensors Water quality Temperature measurement Fish Temperature control

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The Water Quality Online Monitoring System Based on Wireless Sensor Network

The Water Quality Online Monitoring System Based on Wireless...

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International Symposium on Computational Intelligence and Design, ISCID

作者： Qiuchan BAI Jiahao Wu Chunxia JIN Faculty of Automation Huaiyin Institute of Technology Huaian China Faculty of Computer & Software Engineering Huaiyin Institute of Technology Huaian China

ISBN: (数字)9781728184463

ISBN: (纸本)9781728184470

Due to the poor real-time performance of water quality monitoring, secondary pollution, high cost and other issues, this paper proposes to use wireless sensor network technology to design a water quality monitoring system. The system has strong real-time, online monitoring functions, and acquires multiple parameter data that affect water quality, timely and accurately monitor water quality information, prevent water environmental pollution, reduce the impact of water pollution, and meet the requirements of efficient and intelligent water quality.

关键词： Monitoring Wireless sensor networks Zigbee Water quality GSM Temperature sensors Protocols

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Cloud Computing Methods for Leaking Detection of Halogen Pipeline Based On Distributed Terminals

Cloud Computing Methods for Leaking Detection of Halogen Pip...

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International Conference on Robots & Intelligent System (ICRIS)

作者： Min Xu Jianyang Zhao Qiwei Ye Weihong Ding Xiaoqi Zhu Qin Zhang Faculty of Automation Huaiyin Institute of Technology Huaian China Faculty of Computer and Software Engineering Huaiyin Institute of Technology Huaian China

In order to ensure the safe transmission of the brine pipeline, this paper designs a leakage detection terminal based on STM32F7. This terminal uses GPS to added time stamps to the collected data. And each distributed terminal uses second pulse signal of GPS to realize the function of synchronously collecting signals. Finally, the data is transmitted to the cloud computing platform through the 4G wireless transmission module system. This paper uses the S transform algorithm to analyze the characteristics of these transmitted data. S transform algorithm fully extracts the characteristics of the data in the time-frequency-mode domain. The simulation results show that the data generates high-frequency signals at default point. Through the whole system, it can effectively realize real-time monitoring.

关键词： Wireless communication Cloud computing Simulation Pipelines Transforms Real-time systems Timing

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