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The importance of feature selection in online signature verification

Neural Computing and Applications 2024年 1-13页

作者： Szucs, Cintia Lia Kovari, Bence Department of Automation and Applied Informatics Budapest University of Technology and Economics Budapest Hungary

Handwritten signatures are one of the most commonly used biometrics. Because signatures are widely accepted, their verification is a fundamental problem. Online signature verification applies different electronic devices to capture the signatures, which allow the use of dynamic information, such as the pressure or inclination angle of the pen. Therefore, it is much more challenging to forge online signatures. Further derived features can be defined and calculated based on the captured features. The selection of applied features is a crucial step of signature verification. This work aims to analyse the importance of feature selection by comparing the usability of common derived function features using dynamic time warping (DTW) based and Siamese bidirectional long short-term memory (BiLSTM)-based solutions. This paper comprehensively studies the most common function features and their literature background, presents several feature sets including pairs and triplets, compares their effectiveness using different classification approaches, and presents a DTW-based classifier and four Siamese BiLSTM models using two different loss functions. © The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2024.

关键词： Long short-term memory

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A Self-adapting Pixel Antenna - Substrate Lens System for Infrared Frequencies

Periodica Polytechnica Electrical Engineering and Computer S...

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Periodica Polytechnica Electrical Engineering and Computer Science 2025年第1期69卷 14-25页

作者： Shubbar, Mustafa Rakos, Balázs Department of Automation and Applied Informatics Faculty of Electrical Engineering and Informatics Budapest University of Technology and Economics Műegyetem rkp. 3. BudapestH-1111 Hungary

In this work, we propose a concentrator lens - antenna arrangement, potentially suitable for infrared sensing and energy harvesting rectenna systems. The structure consists of a pixel antenna, self-adapting for the direction of the incident infrared radiation, and a concentrator lens, both optimized for the mid-infrared spectrum. The silicon substrate lens is situated above the pixel antenna, enabling the concentration of the incident light on the antenna;silicon was chosen due to its transparency in the IR spectrum. We examine how various parameters of the lens, in conjunction with the different states of the pixel antenna, affects the performance of the system. The simulations show that the gain of the arrangement increases considerably in correlation with the radius of the lens. The results suggest that the energy conversion efficiency of infrared rectenna systems can be enhanced by several orders of magnitude with the utilization of the proposed arrangement. © 2025 budapest university of technology and economics. All rights reserved.

关键词： Rectennas

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Machine Learning and Dynamic Time Warping for Online Signature Verification 32

Machine Learning and Dynamic Time Warping for Online Signatu...

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32nd International Conference on Software, Telecommunications and Computer Networks, SoftCOM 2024

作者： Saleem, Mohammad Budapest University of Technology and Economics Department of Automation and Applied Informatics Budapest Hungary

ISBN: (纸本)9789532901382

Signature verification is a very common task in the field of document analysis used for the identification and validation of individuals. Many approaches can be used for signature classification. Using a machine-learning-based system is one of the most common approaches. This paper uses machine learning to classify signatures as genuine or forged. It also used a dynamic time-warping approach in the preprocessing step to produce data for training purposes. This approach differs from using it in the classification phase, which is a common practice in signature verification. The work targets online signatures, which are obtained using digital devices. Different databases were used to evaluate the accuracy of the verification systems, and four different algorithms were used for classification. The results are very promising. The minimum error rate achieved was 2.09% for the MCYT-100 dataset, 3.34% for the SVC2004 dataset, 1. 6 8 % for the SigComp'11-Chinese dataset, and 3. 6 8 % for the SigComp'11- Dutch dataset. © 2024 university of Split, FESB.

关键词： Adversarial machine learning

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Optimization-based Model Predictive Tube Control for Autonomous Ground Vehicles with Minimal Tuning Parameters

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无人系统（英文） 2023年第1期11卷 93-108页

作者： Adorjan Kovacs Istvan Vajk Department of Automation and Applied Informatics Faculty of Electrical Engineering and InformaticsBudapest University of Technology and EconomicsMegyetem rkp.3H-1111 BudapestHungary

The trajectory planning and tracking problem are critical points of intelligent vehicles concerning their safety and *** these parts are separated,interactions should be made between them,especially when sudden changes and disturbances *** paper presents a method that integrates the two parts using a cascade ***,the proposed method deals with the interaction between the lateral and the longitudinal trajectory based on dynamical *** whole problem is handled using the model predictive method based on online *** system receives the path borders as input and generates the control requests for the actuators on its *** configuration space of the system can be maximized to gain stability by handling the lateral-longitudinal parts and the trajectory planning and tracking in one complex *** main advantage of the proposed approach is that the optimization problem in the predictive method is formulated so that the path and dynamics are considered equality and inequality constraints,and the cost function includes only a physical phenomenon to be minimized without tuning *** evaluation of the proposed algorithm is presented in this paper based on simulation and real-time measurements results.

关键词： Path planning path following autonomous car convex optimization model predictive control internal model control

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Enhanced Indoor Mapping via Integration of Lidar and HoloLens 2 Data Using Iterative Closest Point Algorithm 22

Enhanced Indoor Mapping via Integration of Lidar and HoloLen...

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22nd IEEE International Symposium on Intelligent Systems and informatics, SISY 2024

作者： Szalka, Panka Hideg, Attila Budapest University of Technology and Economics Faculty of Electrical Engineering and Informatics Department of Automation and Applied Informatics Budapest Hungary

ISBN: (纸本)9798350385601

This study presents an innovative method to improve the accuracy of indoor mapping by deploying and integrating a sensor that transmits two-dimensional data with a three-dimensional mesh created by another device. The Iterative Closest Point algorithm was used to coordinate the different data sets and transform their different coordinate systems into a common indoor map. Prior to this, rigorous image cleaning and matching processes are conducted to ensure the quality of the data used. The effectiveness of this methodology has been validated through multiple tests using a Lidar scanner and a HoloLens 2 Augmented Reality device. This method not only offers potential for enhancing indoor navigation and safety protocols like emergency evacuation but also presents opportunities for advancing asset tracking and other applications. © 2024 IEEE.

关键词： Indoor positioning systems

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Real-Time Evaluation of Weighting Factorless Predictive Control of LCL Filter Equipped Grid-Side Converters using Sorting Networks

Real-Time Evaluation of Weighting Factorless Predictive Cont...

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2024 International Exhibition and Conference for Power Electronics, Intelligent Motion, Renewable Energy and Energy Management, PCIM Europe 2024

作者： Bándy, Kristóf Stumpf, Péter Süto, Zoltán Department of Automation and Applied Informatics Faculty of Electrical Engineering and Informatics Budapest University of Technology and Economics Hungary

ISBN: (纸本)9783800762620

A novel multi-cost function model-based finite-set predictive control method is presented for grid-side converters equipped with LCL filters. This approach aims to overcome the tedious tuning of weighting factors. In the method, the cost functions are established based on various state variables and their references. Then the control options are ranked based on their performance in each of the cost functions. This ranking score determines the selection of the optimal control action. The control method is validated in a low-cost custom Hardware-in-the-Loop (HIL) environment using model-based rapid-prototyping tools of Matlab/Simulink. Simulation and measurement results show the viability of the method. © VDE VERLAG GMBH · Berlin · Offenbach.

关键词： Hardware-in-the-loop simulation

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Optimal Selection of Switch Model Parameters for ADC-Based Full-Bridge Converter

Optimal Selection of Switch Model Parameters for ADC-Based F...

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2023 IEEE International Conference on Electrical, Computer and Energy Technologies, ICECET 2023

作者： Alsarayreh, Saif Süto, Zoltán University of Technology and Economics Department of Automation and Applied Informatics Budapest Budapest Hungary

ISBN: (纸本)9798350327816

The incorporation of real-time Hardware-In-the-Loop (HIL) simulators has become one of the pillars of the power electronics control design cycle. This integration is necessary to verify the effectiveness of controller implementations. Despite the rapid evolution in FPGA devices' computational capacity employed by Hardware-in-the-Loop (HIL) tools, developers are consistently faced with the need to strike a balance between acceptable accuracy and the practicality of implementing models and techniques. The methodology presented in this paper is for implementing a full-bridge converter using the Associate Discrete Circuit (ADC) model, specifically designed for real-time simulator applications. Furthermore, this study presents a novel methodology for parameter selection of (ADC) parameters utilizing the Artificial Bee Colony algorithm (ABC). The utilization of the ADC-based model facilitates the establishment of a uniform converter topology during simulation, irrespective of the switch states. The simulation results demonstrate the effectiveness of the introduced methodology in selecting optimal parameters for an ADC switch-based full-bridge converter, reducing overshoot in the converter's output voltage and current. © 2023 IEEE.

关键词： Artificial bee colony field-programmable gate array Full-bridge converter Optimization algorithm Real-time Simulation Terms-Associate Discrete Circuit

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Fault Diagnosis Using Artificial Neural Network for Two-Level VSI in PMSM Drive System

Fault Diagnosis Using Artificial Neural Network for Two-Leve...

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2023 IEEE International Conference on Electrical, Computer and Energy Technologies, ICECET 2023

作者： Alsarayreh, Saif Süto, Zoltán Budapest University of Technology and Economics Department of Automation and Applied Informatics Budapest Hungary

ISBN: (纸本)9798350327816

A permanent magnet synchronous motor's (PMSM) drive system depends heavily on the voltage source inverter (VSI). However, the VSI shows vulnerability to faults during operation, especially when it comes to open circuit switch faults, which are the most frequent and have the most significant negative impact on the drive system. In order to diagnose Open Circuit Faults (OCF) in the Voltage Source Inverter (VSI) of a three-phase permanent magnet synchronous motor drive system, this work employs the vector average current technique in Clark's transformation and an artificial neural network. Diagnostic variables are computed based on the current distortion to gather details about the fault. An artificial neural network (ANN) is put to use to process the fault information in order to determine and locate the specific location of the faulty switch. The study's simulation results show that the methodology employed effectively identifies and localises open circuit faults in a two-level, three-phase inverter. © 2023 IEEE.

关键词： Artificial Neural Network Fault Detection Open Circuit Fault Permanent Magnet Synchronous Motor Voltage Source Inverter

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An Overview of Drones Communication, Application and Challenge in 5G Network 6

An Overview of Drones Communication, Application and Challen...

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6th Iraqi International Conference on Engineering technology and its Applications, IICETA 2023

作者： Almaameri, Ihab Blázovics, László Budapest University of Technology and Economics Department of Automation and Applied Informatics Budapest Hungary

ISBN: (纸本)9798350303339

Unmanned aerial vehicles (UAVs), also known as drones, are recently gaining increased research attention across various fields due to their flexibility and application potential. Drones have become increasingly popular in recent years due to their versatility and ability to perform tasks that were previously challenging or impossible. However, the full potential of drone technology has not been realized due to limitations in their communication and control systems. The integration of drone networks into a 5G environment has the potential to transform the capabilities of drones, providing high-speed, low-latency, and reliable communication and control capabilities. In this review paper, we provide an overview of the integration of drone networks into a 5G environment, discussing the technical aspects, potential applications, and challenges of this integration. We also examine the benefits of using 5G networks for drone operations, such as increased range, improved accuracy, and enhanced safety. Finally, we identify future research directions for the integration of drone networks into a 5G environment, highlighting the need for further research in areas such as drone security, energy efficiency, and spectrum management. Overall, this review paper provides a valuable resource for understanding the potential of drones in a 5G network and the challenges that must be addressed to fully realize this potential. © 2023 IEEE.

关键词： Drones

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Autonomous Exploration Using a Tree Structure For Goal Selection 17

Autonomous Exploration Using a Tree Structure For Goal Selec...

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17th IEEE International Symposium on applied Computational Intelligence and informatics, SACI 2023

作者： Abonyi-Toth, Barbara Nagy, Akos Budapest University of Technology and Economics Department of Automation and Applied Informatics Budapest Hungary

ISBN: (纸本)9798350321104

Autonomous exploration of unknown environments using unmanned robots is a widely researched problem of our days. The focus of this paper is to provide a novel goal-selection method in response to the problems of the simple greedy goal selection algorithm. The presented method uses a tree structure built from the detected frontiers and selects the next goal of exploration using a depth-first search on the expanding tree. This prevents the exploring robot from leaving half-explored areas and backtracking to them later in the exploration. The method is tested in two simulated environments. The results are compared to those achieved using a simple greedy goal selection algorithm. © 2023 IEEE.

关键词： Trees (mathematics)

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