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Exploring Deep Learning Methods for computer Vision Applications across Multiple Sectors:Challenges and Future Trends

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computer Modeling in engineering & Sciences 2024年第4期139卷 103-141页

作者： Narayanan Ganesh Rajendran Shankar Miroslav Mahdal Janakiraman SenthilMurugan Jasgurpreet Singh Chohan Kanak Kalita School of Computer Science and Engineering Vellore Institute of TechnologyChennai600127India Department of Computer Science and Engineering Koneru Lakshmaiah Education FoundationVaddeswaram522502India Department of Control Systems and Instrumentation Faculty of Mechanical EngineeringVSB-Technical University of OstravaOstrava70800Czech Republic Department of Computer Science and Engineering Vel Tech High Tech Dr.Rangarajan Dr.Sakunthala Engineering CollegeChennai600062India Department of Mechanical Engineering and University Centre for Research&Development Chandigarh UniversityMohali140413India Department of Mechanical Engineering Vel Tech Rangarajan Dr.Sagunthala R&D Institute of Science and TechnologyAvadi600062India

computer vision(CV)was developed for computers and other systems to act or make recommendations based on visual inputs,such as digital photos,movies,and other *** learning(DL)methods are more successful than other traditional machine learning(ML)methods *** techniques can produce state-of-the-art results for difficult CV problems like picture categorization,object detection,and face *** this review,a structured discussion on the history,methods,and applications of DL methods to CV problems is *** sector-wise presentation of applications in this papermay be particularly useful for researchers in niche fields who have limited or introductory knowledge of DL methods and *** review will provide readers with context and examples of how these techniques can be applied to specific areas.A curated list of popular datasets and a brief description of them are also included for the benefit of readers.

关键词： Neural network machine vision classification object detection deep learning

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Making children read more and better by integrating natural language processing and gamification techniques into mobile applications 24

Making children read more and better by integrating natural ...

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24th International Conference on control Systems and computer Science, CSCS 2023

作者： Voicu, George Catalin Ciolofan, Sorin N. Dragoicea, Monica Manager Emag Bucharest Romania Politehnica University of Bucharest Department of Computer Science Bucharest Romania Politehnica University of Bucharest Department of Automatic Control and Systems Engineering Bucharest Romania

ISBN: (纸本)9798350313390

It is well known that nowadays children tend to spend lot of time playing games on mobile devices at the expense of reading books. The current research aims to explore ways to design and develop a mobile application, attractive for children, that uses voice recognition technology and gamification techniques to help children read more and better and to track the progress of reading. The application is implemented with Flutter, Dart and Firebase and is addressed to children, the books being made available in encyclopedia format. By integrating technologies such as NLP and gamification the application aims to improve reading fluency among children, but also to give them the opportunity to accumulate new and exciting information in the same time. © 2023 IEEE.

关键词： Human computer interaction

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Weighting Attributes Based on the Greedy Algorithm Properties 28th

Weighting Attributes Based on the Greedy Algorithm Propertie...

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28th International Conference on Knowledge Based and Intelligent information and engineering Systems, KES 2024

作者： Zielosko, Beata Stanczyk, Urszula Jablonski, Kamil University of Silesia in Katowice Institute of Computer Science Bedzinska 39 Sosnowiec41-200 Poland Department of Computer Graphics Vision and Digital Systems Faculty of Automatic Control Electronics and Computer Science Silesian University of Technology Akademicka 2A Gliwice44-100 Poland

Estimation of importance for considered features is an important issue for any knowledge exploration process and it can be executed by a variety of approaches. In the research reported in this study, the primary aim was the development of a methodology for creating attribute rankings. Based on the properties of the greedy algorithm for inducing decision rules, a new application of this algorithm has been proposed. Instead of constructing a single ordering of features, attributes were weighted multiple times. The input datasets were discretised with several algorithms representing supervised and unsupervised discretisation approaches. Each resulting discrete data variant was exploited to construct a ranking of attributes. The effectiveness of the obtained rankings was confirmed through a rule filtering process governed by weighted attributes. The methodology was applied to the stylometric task of authorship attribution. The experimental outcomes demonstrate the value of the proposed research method, as it generally led to improved predictions while taking into account a noticeably decreased sets of attributes and decision rules. © 2024 The Authors.

关键词： Consensus algorithm

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Stereographic Projection of Probabilistic Frequency-Domain Uncertainty 63

Stereographic Projection of Probabilistic Frequency-Domain U...

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63rd IEEE Conference on Decision and control, CDC 2024

作者： Nystrom, Anton Renganathan, Venkatraman Cantoni, Michael Lund University Faculty of Engineering Sweden Cranfield University United Kingdom Lund University Department of Automatic Control - Lth Sweden Lund University Elliit Strategic Research Area Sweden The University of Melbourne Department of Electrical and Electronic Engineering Australia

ISBN: (纸本)9798350316339

This paper investigates the stereographic projection of points along the Nyquist plots of single input single output (SISO) linear time invariant (LTI) systems subject to probabilistic uncertainty. At each frequency, there corresponds a complex-valued random variable with given probability distribution in the complex plane. The chordal distance between the stereographic projections of this complex value and the corresponding value for a nominal model, as per the well-known ν-Gap metric of Vinnicombe, is also a random quantity. The main result provides the cumulative density function (CDF) of the chordal distance at a given frequency. Such a stochastic distance framework opens up a fresh and a fertile research direction on probabilistic robust control theory. © 2024 IEEE.

关键词： Frequency domain analysis

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Metaheuristic Optimization Algorithm for Signals Classification of Electroencephalography Channels

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computers, Materials & Continua 2022年第6期71卷 4627-4641页

作者： Marwa M.Eid Fawaz Alassery Abdelhameed Ibrahim Mohamed Saber Department of Communications and Electronics Delta Higher Institute of Engineering and TechnologyMansoura35111Egypt Department of Computer Engineering College of Computers and Information TechnologyTaif UniversityTaif21944Saudi Arabia Computer Engineering and Control Systems Department Faculty of EngineeringMansoura UniversityMansoura35516Egypt Department of Electronics and Communications Engineering Faculty of EngineeringDelta University for Science and TechnologyMansoura11152Egypt

Digital signal processing of electroencephalography(EEG)data is now widely utilized in various applications,including motor imagery classification,seizure detection and prediction,emotion classification,mental task classification,drug impact identification and sleep state *** the increasing number of recorded EEG channels,it has become clear that effective channel selection algorithms are required for various *** Whale Optimization Method(Guided WOA),a suggested feature selection algorithm based on Stochastic Fractal Search(SFS)technique,evaluates the chosen subset of *** may be used to select the optimum EEG channels for use in Brain-computer Interfaces(BCIs),the method for identifying essential and irrelevant characteristics in a dataset,and the complexity to be *** enables(SFS-Guided WOA)algorithm to choose the most appropriate EEG channels while assisting machine learning classification in its tasks and training the classifier with the ***(SFSGuided WOA)algorithm is superior in performance metrics,and statistical tests such as ANOVA and Wilcoxon rank-sum are used to demonstrate this.

关键词： Signals metaheuristics optimization feature selection multilayer perceptron support vector machines

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Integration of Industrial Automation and IoT Devices on the Example of the Assembly Station with the Astorino Educational Robot 4th

Integration of Industrial Automation and IoT Devices on the ...

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4th International Conference on Intelligent Systems in Production engineering and Maintenance, ISPEM 2023

作者： Ćwikla, Grzegorz Kalinowski, Krzysztof Kciuk, Marek Gold, Michal Waluśkiewicz, Marek Sladek, Michal Tlolka, Jaroslaw Woźnica, Robert Wlazlo, Aleksander Faculty of Mechanical Engineering Silesian University of Technology Konarskiego 18A Gliwice44-100 Poland Faculty of Electrical Engineering Silesian University of Technology Akademicka 10A Gliwice44-100 Poland Faculty of Automatic Control Electronics and Computer Science Silesian University of Technology Akademicka 16 Gliwice44-100 Poland

ISBN: (纸本)9783031442810

The article presents an automated assembly station designed by students as part of Project Based Learning. The task of the project was to familiarize with the issues of integration of automation and control elements operating in various standards in order to implement the idea of Industry 4.0. The main elements of the station are the Astorino educational robot, gripper, servo drive and other professional elements of industrial automation and IoT systems. Raspberry PI, microcontrollers, etc. are also used. The assembly process of the product in the configuration in accordance with the user’s order is carried out at the station, quality control is carried out during the process using a vision system and various sensors. © 2024, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Data acquisition

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DESIGNING A FUZZY controlLER FOR THE AUTOMATION OF AN IRRIGATION SYSTEM

UPB Scientific Bulletin, Series C: Electrical Engineering an...

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UPB Scientific Bulletin, Series C: Electrical engineering and computer Science 2023年第1期85卷 65-76页

作者： Bostan, Alexandra Dobrescu, Radu Hossu, Daniela Hossu, Andrei Faculty of Automatic Control and Computer Science University POLITEHNICA of Bucharest Romania Automatic Control and Industrial Informatics Department University POLITEHNICA of Bucharest Romania

The paper presents a solution for an irrigation controller based on the fuzzy-logic methodology. First, it describes the general problem of irrigation. Then, it discusses the physical control model. The precious irrigation is great significance for arid and semiarid area. In this paper, a fuzzy control algorithm was proposed to make an optimal irrigation strategy based on the actual measured soil humidity. In this paper, the fuzzy control algorithm was introduced in detail which included the setting of input and output, the selection of membership function and the setting of fuzzy rules. Following the discussion and the formal presentation of the fuzzy controller, the paper provide examples that will show the simplicity in designing and constructing such a system and other advantages of using fuzzy logic in the feedback control problem. © 2023, Politechnica University of Bucharest. All rights reserved.

关键词： Irrigation

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Retinal disorder diagnosis based on hybrid deep learning models

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Multimedia Tools and Applications 2025年 1-25页

作者： Sedik, Ahmed El-Shafai, Walid El-Hag, Noha A. El-Banby, Ghada M. Abd El-Samie, Fathi E. Smart Systems Engineering Laboratory College of Engineering Prince Sultan University Riyadh11586 Saudi Arabia Department of the Robotics and Intelligent Machines Faculty of Artificial Intelligence Kafrelsheikh University Kafr el-Sheikh Egypt Computer Science Department Prince Sultan University Riyadh11586 Saudi Arabia Department of Electronics and Electrical Communications Engineering Faculty of Electronic Engineering Menoufia University Menouf32952 Egypt The Higher Institute of Commercial Sciences Algarbia Al Mahalla Al Kubra31951 Egypt Department of Industrial Electronics and Control Engineering Faculty of Electronic Engineering Menoufia University Menouf32952 Egypt Department of Information Technology College of Computer and Information Sciences Princess Nourah Bint Abdulrahman University P.O. Box 84428 Riyadh11671 Saudi Arabia

Anomaly detection from medical images is badly needed for automated diagnosis. For example, medical images obtained with several modalities, such as magnetic resonance (MR) and confocal microscopy, need to be classified for anomaly detection. The MR images may contain tumors that need to be detected with anomaly detection techniques. In MR imaging, brain tumors are represented as areas composed of abnormal cells that need to be detected. On the other hand, confocal microscopy can be used for retinal imaging. Hence, there is a need to apply classification techniques for diagnosing diseases of the eye, such as Diabetic Retinopathy (DR), which leads to exudates in different regions of the retina. The detection of exudates is necessary for the diagnosis of DR. In this paper, two models are presented for the classification of MR and retinal images. Much research has been done in this area, but it did not achieve high accuracy of classification in an acceptable time. In addition, the previous models did not consider both types of image modalities considered in this paper. The suggested models are Convolutional Neural Network (CNN) and Convolutional Long Short-Term Memory (Conv-LSTM). They are used to classify normal and abnormal cases of both brain tumor and DR diseases. The CNN model is composed of six convolutional layers and six max-pooling layers. A soft-max activation function takes the classification decision. The proposed Conv-LSTM model is composed of three stages: pre-processing, feature extraction, and classification. The deep learning model performance is better than those of traditional networks. The CNN gives an accuracy of 94.26% for DR classification and 95.8% for brain tumor classification, while the Conv-LSTM gives the maximum accuracy of 96.41% for DR classification and 97.4% for brain tumor classification. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2025.

关键词： Confocal microscopy

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Trajectory Following in Differential Drive Mobile Platform

Trajectory Following in Differential Drive Mobile Platform

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Electrical, Electronic and Computing engineering (IcETRAN), International Conference on

作者： Anđela Jovanović Vladimir Sibinović Vladimir Mitić Boban Veselić Department of Automatic Control Faculty of Electronic Engineering University of Niš Niš Serbia

ISBN: (数字)9798350386998

ISBN: (纸本)9798350387001

This paper considers a trajectory tracking problem in motion control of a mobile platform. The platform is designed to have differential drive, Arduino microcontroller, Bluetooth connectivity and is battery powered, thus representing a complete mechatronic system. The task at this stage was to provide the platform motion along simple desired trajectories, such as straight lines and curves. During its motion, the platform draws its trajectory on the surface, upon which motion accuracy can be evaluated. Odometry approach is used in solving this task where each wheel motor is driven within a cascaded control structure with conventional digital controllers. Experimental results of several tests are presented and analyzed.

关键词： Mechatronics Bluetooth Trajectory tracking Microcontrollers Wheels Motors Trajectory

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Hydrodynamic and Static Stability Analysis of a Hybrid Offshore Wind-Wave Energy Generation: An Expansion of Semisubmersible Floating Wind Turbine Concept 15th

Hydrodynamic and Static Stability Analysis of a Hybrid Offsh...

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15th European Wave and Tidal Energy Conference, EWTEC 2023

作者： Aboutalebi, Payam Garrido, Aitor J. Garrido, Izaskun Nguyen, Dong Trong Gao, Zhen Department of Marine Technology Trondheim7491 Norway Automatic Control Group–ACG Institute of Research and Development of Processes–IIDP Department of Automatic Control and Systems Engineering Faculty of Engineering of Bilbao University of the Basque Country–UPV/EHU Spain School of Naval Architecture Ocean and Civil Engineering Shanghai Jiao Tong University Shanghai200240 China

Marine structures like Floating Wind Turbine (FWT) is exposed to the oncoming waves and wind that can cause oscillatory motions within the system. These undesired oscillations can have negative impacts on the efficiency of the system, reduce its lifespan, hinder energy extraction, increase stress levels, and raise maintenance costs. To mitigate these negative impacts, the integration of Wave Energy Converters (WECs) into the FWT system has been proposed. This hybrid system may be capable of extracting coupled wind-wave energy and transferring electrical power to the shared grid. This paper presents an investigation of the use of Oscillating Water Columns (OWCs), a type of WECs, within a FWT system. The purpose of using an OWC is to increase the hydrodynamic damping and reduce the resonant motions of the floating wind turbines under environmental loads, including both wind and wave loads. This is because the wave energy from OWC would be very small as compared to the wind energy. However, OWCs can provide a damping source for reducing the resonant motions of the floater, especially the pitch resonant motions. This would be very beneficial for the power performance of the floating w ind turbine and the structural design of the floater. T he p urpose of this paper is to redesign the original FWT platform to accommodate the additional OWCs by considering the hydrostatic stability and hydrodynamics since the new elements, the OWCs, can significantly change the response of the platform. The redesign of the original FWT involves the integration of OWCs within two out of three columns of an existing semisubmersible platform for a 12 MW FWT. To do this, two moonpools, which are consistent with OWC air chambers, have been created within two columns of the FWT. The water ballast was designed for the columns with and without OWCs. After that the redesign is done hydrostatic stability and hydrodynamics analyses are evaluated. The hydrodynamics properties are discussed in terms o

关键词： Tidal power

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