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12th Mediterranean Conference on Embedded Computing, MECO 2023

作者： Tihak, Amina Boskovic, Dusanka University of Sarajevo Faculty of Electrical Engineering Department of Automatic Control and Electronics Sarajevo Bosnia and Herzegovina

ISBN: (纸本)9798350322910

The paper evaluates statistical significance of the differences in the feature values necessary to differentiate the signals corresponding to cardiac arrhythmia (AR) and atrial fibrillation (AF). The initial set of heart rate variability (HRV) features includes time and frequency domain metrics, as well as geometric metrics based on the Poincare diagram. Due to non-uniformity of the heart rate signal, frequency domain features are calculated using two approaches: the Lomb-Scargle method for spectral analysis for non-uniform signals, and Welch method for uniform signals, but after the signal interpolation and resampling. Selection of an appropriate statistical test was depending on the distribution of feature values. Normal distribution allowed use of parametric ANOVA test and otherwise non-parametric Wilcoxon-Mann-Whitney test were used. The statistical tests indicated statistically significant difference between the two observed groups of signals of interest with respect to the evaluated feature. The success of the classification depends on the well-chosen features according to their importance. In the paper, statistical tests resulted in selection of 27 features out of the initial 51. The proposed set of features could be used for the classification between the AR and AF signals to assist diagnosis of the mentioned heart diseases. © 2023 IEEE.

关键词： Statistical tests

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Image Enhancement for Facial Landmark Detection 21

Image Enhancement for Facial Landmark Detection

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21st RoEduNet Conference on Networking in Education and Research, RoEduNet 2022

作者： Ciuntu, Victor Chiornita, Traian Boiangiu, Costin-Anton Tarba, Nicolae Voncila, Mihai-Lucian Rosner, Daniel Politehnica University Faculty of Automatic Control and Computers Computer Science and Engineering Department Bucharest Romania

ISBN: (数字)9781665455282

ISBN: (纸本)9781665455282

Facial landmark detection (FLD) is a field of study in computer vision that specializes in detecting and tracking key points from human faces. There are many applications, such as detecting a human's head pose (position and rotation), tracking whether drivers are paying attention or not, applying augmented reality, etc. This paper proposes to evaluate and decide what are the optimal techniques of image enhancement that can be used to improve different algorithms of FLD. After proposing different pipelines of contrast enhancement and grayscale conversion to enhance the image before applying the FLD algorithm, the results show that the performance will not increase drastically if an image enhancement pipeline is used, but for the reason that this step will not consume a lot of time in the process of detection, it is a step worth considering. © 2022 IEEE.

关键词： Face recognition

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Increasing the security of web applications by using smartphones 21

Increasing the security of web applications by using smartph...

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21st RoEduNet Conference on Networking in Education and Research, RoEduNet 2022

作者： Contasel, Cristian Tranca, Dumitru-Cristian Palacean, Alexandru-Viorel University Politehnica of Bucharest Bucharest Faculty of Automatic Control and Computers Department of Computer Engineering Romania

ISBN: (数字)9781665455282

ISBN: (纸本)9781665455282

The web applications security systems often use the authentication strategy and credentials to assess the identity of the user. Based on the credentials, the system is able to claim the identity of the user. Also, the authenticity of identity is claimed based on authentication strategy. This paper analyzes and compares different strategies used to enforce the web applications security systems by using location and biometric features of the smartphones to provide two-way authentications. © 2022 IEEE.

关键词： Smartphones

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Complete OCR Solution for Image Analysis of World War 2 Documents 21

Complete OCR Solution for Image Analysis of World War 2 Docu...

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21st RoEduNet Conference on Networking in Education and Research, RoEduNet 2022

作者： Gradinaru, Mihai Negru, Andrei Boiangiu, Costin-Anton Tarba, Nicolae Voncila, Mihai-Lucian Deaconescu, Razvan Adrian Politehnica University Faculty of Automatic Control and Computers Computer Science and Engineering Department Bucharest Romania

ISBN: (数字)9781665455282

ISBN: (纸本)9781665455282

The field of Optical Character Recognition (OCR) consists of techniques that are mainly focused on document image analysis. Aside from generating significant speedups of everyday procedures, OCR has a considerable role in the preservation of historical sources of information. Most of the World War 2 (WW2) documents are of great importance, especially with applications in virtual archives, museums, and research. The situation asks for an efficient, yet not aggressive, transcribing method using OCR tools. This paper describes an approach in the context of the given problem. The focus is oriented towards extracting the information from documents affected by their age, but with simpler structures, mainly split into paragraphs, such as letters and military reports. The approach is based on combining the results of multiple OCR engines, with the final objective of achieving better performance compared to the individual performance of each engine. © 2022 IEEE.

关键词： Engines

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Increasing communication security for Bluetooth Medical Devices in eHealth systems 21

Increasing communication security for Bluetooth Medical Devi...

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21st RoEduNet Conference on Networking in Education and Research, RoEduNet 2022

作者： Contasel, Cristian Tranca, Dumitru-Cristian Palacean, Alexandru-Viorel Rosner, Daniel University Politehnica of Bucharest Faculty of Automatic Control and Computers Department of Computer Engineering Bucharest Romania

ISBN: (数字)9781665455282

ISBN: (纸本)9781665455282

The market of Medical Devices has an annual growth rate perspective of 5.4% in the 2022 - 2028 period. The growth rate is mainly supported by the increased usage of devices for chronic diseases prevention and for remote patient monitoring. The growth rate is also supported by the population's appetite for mobile devices. The continuously growing number of mobile devices has led to an increase in the number of cyber-attacks against them. In this paper we present Personal Medical Hub, an optimized security solution for Bluetooth enabled medical devices, that enhances data privacy and is aimed to offer protection against man-in-the-middle attacks and other security breaches and backdoors. © 2022 IEEE.

关键词： Cybersecurity

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TCIP: Transformed Colour Intensity Profiles analysis for fault detection in power line insulators

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Multimedia Tools and Applications 2025年第8期84卷 4503-4534页

作者： Tomaszewski, Michal Gasz, Rafal Kasana, Singara Singh Osuchowski, Jakub Singh, Simranjit Zator, Slawomir Department of Computer Science Faculty of Electrical Engineering Automatic Control and Informatics Opole University of Technology Prószkowska 76 Opole45-758 Poland Department of Computer Science and Information Technology Central University of Haryana Haryana Mahendergarh123031 India Department of Information Technology Dr B. R. Ambedkar National Institute of Technology Punjab Jalandhar India Department of Safety Engineering and Technical Systems Faculty of Production Engineering and Logistics Opole University of Technology Prószkowska 76 Opole45-758 Poland

In response to the escalating demand for electricity, the aging process and inherent failures in power lines have become unavoidable challenges in their operational integrity. This research addresses the imperative need for a robust method to detect damage in power insulator disc images, introducing a novel feature extraction technique grounded in color intensity profile transformation and ensemble learning. For the purposes of the research, a specific dataset was developed based on publicly available images of power insulators. The collection consists of 9232 images of insulator discs which included 2184 images of damaged discs. The discernible damages include breakages and burnouts. Two distinct analysis variants were employed. In the first variant (V1), two classification groups were selected: disc with damages and disc without damages. In the second variant (V2), three classification groups were selected: discs without damage, broken discs, and burnout discs. The described research was divided into two successive stages. In the first of them (S1), the transformed color intensity profiles for the prepared data set were built and various machine learning models for their classification were trained and evaluated. In the next stage (S2), previously developed, highest efficient machine learning models, were used to make the detection of various damaged types of overhead line insulator discs. For the first stage of research high-performance results and a high value of the F1 score parameters were obtained (F1 score = 0.999 for the first variant (S1V1) and F1 score = 0.992 for the second variant (S1V2). In the second stage of research and the first variant (S2V1), the highest result of the F1 score was 0.932 and for the second variant (S2V2) F1 score was 0.930. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024.

关键词： Feature extraction

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SightAid: empowering the visually impaired in the Kingdom of Saudi Arabia (KSA) with deep learning-based intelligent wearable vision system

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Neural Computing and Applications 2024年第19期36卷 11075-11095页

作者： Talaat, Fatma M. Farsi, Mohammed Badawy, Mahmoud Elhosseini, Mostafa Machine Learning Department Faculty of Artificial Intelligence Kafrelsheikh University Kafrelsheikh Egypt Faculty of Computer Science & amp Engineering New Mansoura University Gamasa35712 Egypt College of Computer Science and Engineering Taibah University Yanbu46421 Saudi Arabia Computers and Control Systems Engineering Department Faculty of Engineering Mansoura University Mansoura35516 Egypt Computer Science and Information Department Applied College Taibah University Madinah46537 Saudi Arabia

In the Kingdom of Saudi Arabia, visual impairment poses significant challenges for approximately 17.5% of school-aged children, mainly due to refractive errors. These challenges extend to everyday navigation, environmental interaction, and overall life quality. Motivated by the desire to empower visually impaired individuals, who face navigational limitations, difficulties in object recognition, and inadequate assistance from traditional technologies, we propose SightAid. This innovative wearable vision system utilizes a deep learning-based framework, addressing the gaps left by current assistive solutions. Traditional methods, such as canes and GPS devices, often fail to meet the nuanced and dynamic needs of the visually impaired, especially in accurately identifying objects, understanding complex environments, and providing essential real-time feedback for independent navigation. SightAid comprises a seven-phase framework involving data collection, preprocessing, and training of a sophisticated deep neural network with multiple convolutional and fully connected layers. This system is integrated into smart glasses with augmented reality displays, enabling real-time object detection and recognition. Interaction with users is facilitated through audio or haptic feedback, informing them about the location and type of objects detected. A continuous learning mechanism, incorporating user feedback and new data, ensures the system's ongoing refinement and adaptability. For performance assessment, we utilized the MNIST dataset, and an Indoor Objects Detection dataset tailored for the visually impaired, featuring images of everyday objects crucial for safe indoor navigation. SightAid demonstrates remarkable performance with accuracy up to 0.9874, recall values between 0.98 and 0.99, F1-scores ranging from 0.98 to 0.99, and AUC-ROC values reaching as high as 0.9999. These metrics significantly surpass those of traditional methods, highlighting SightAid's potential to substan

关键词： Object recognition

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Novel Framework of Segmentation 3D MRI of Brain Tumors

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computers, Materials & Continua 2023年第2期74卷 3489-3502页

作者： Ibrahim Mahmoud El-Henawy Mostafa Elbaz Zainab H.Ali Noha Sakr Department of Computer Science Faculty of Computers and InformaticsZagazig UniversityZagazigEgypt Department of Computer Science Faculty of Computers and InformaticsKafrelsheikh UniversityKafrelsheikhEgypt Department of Embedded Network Sys.and Tec. Faculty of Artificial IntelligenceKafrelsheikh UniversityKafrelsheikhEgypt Computers Engineering and Control Systems Department Faculty of EngineeringMansoura UniversityMansouraEgypt

Medical image segmentation is a crucial process for computer-aided diagnosis and *** image segmentation refers to portioning the images into small,disjointed parts for simplifying the processes of analysis and *** and speckle noise are different types of noise in magnetic resonance imaging(MRI)that affect the accuracy of the segmentation process ***,image enhancement has a significant role in MRI *** paper proposes a novel framework that uses 3D MRI images from Kaggle and applies different diverse models to remove Rician and speckle noise using the best possible noise-free *** proposed techniques consider the values of Peak Signal to Noise Ratio(PSNR)and the level of noise as inputs to the attention-U-Net model for segmentation of the *** framework has been divided into three stages:removing speckle and Rician noise,the segmentation stage,and the feature extraction *** framework presents solutions for each problem at a different stage of the *** the first stage,the framework uses Vibrational Mode Decomposition(VMD)along with Block-matching and 3D filtering(Bm3D)algorithms to remove the ***,the most significant Rician noise-free images are passed to the three different methods:Deep Residual Network(DeRNet),Dilated Convolution Auto-encoder Denoising Network(Di-Conv-AE-Net),andDenoising Generative Adversarial Network(DGAN-Net)for removing the speckle *** Bm3D have achieved PSNR values for levels of noise(0,0.25,0.5,0.75)for reducing the Rician noise by(35.243,32.135,28.214,24.124)and(36.11,31.212,26.215,24.123)*** framework also achieved PSNR values for removing the speckle noise process for each level as follows:(34.146,30.313,28.125,24.001),(33.112,29.103,27.110,24.194),and(32.113,28.017,26.193,23.121)forDeRNet,Di-Conv-AE-Net,and DGAN-Net,*** experiments that have been conducted have proved the efficiency of the proposed framework a

关键词： MRI Rician noise speckle noise segmentation deep learning

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User Input Search - Custom Motion Estimation Algorithm Optimized for UAVs 46

User Input Search - Custom Motion Estimation Algorithm Optim...

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46th ICT and Electronics Convention, MIPRO 2023

作者： Benjak, J. Hofman, D. Faculty of Electrical Engineering and Computing Department of Control and Computer Engineering Zagreb Croatia

ISBN: (纸本)9789532331042

Unmanned aerial vehicle technology is growing rapidly as it finds its application in the various industries, including military & defense, agriculture, logistics, transportation, healthcare, entertainment and many others. One of the fastest growing industries including drones is the entertainment industry. More specifically, First Person View (FPV) piloting has become a popular sport which attracts huge masses. In FPV systems, the pilot wears FPV goggles and controls the drone using a controller, and the drone transmits video data to the goggles in real time. Since drones usually fly very quickly, the video quality in terms of resolution, compression artefacts and end-to-end delay must be maintained. This paper explores the idea of optimizing the Motion Estimation (ME) algorithm of existing High Efficiency Video Coding (HEVC) algorithms by utilizing user input from the controller. For example, if the drone is directed to hover to the left, then it would make sense to search for the most similar blocks in the previous video frame only on the left side of the referent block. For the purpose of this research, a HEVC video coder was customized to receive additional input besides the video data - the user input from the controller, or in other words, drone movement directions. We call this ME algorithm User Input Search (UIS). Our UIS algorithm is compared with the standard ME algorithms and its efficiency is tested. © 2023 MIPRO Croatian Society.

关键词： Real time systems

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Modeling of Thermal Processes in a Microcontroller System with the Use of Hybrid, Fractional Order Transfer Functions 21st

Modeling of Thermal Processes in a Microcontroller System wi...

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21st Polish control Conference, PCC 2023

作者： Oprzedkiewicz, Krzysztof Rosol, Maciej Mitkowski, Wojciech Department of Automatic Control and Robotics Faculty of Electrical Engineering Automatic Control Informatics and Biomedical Engineering AGH University of Science and Technology al. A Mickiewicza 30 Krakow30-059 Poland

ISBN: (纸本)9783031351693

In the paper the problem of modeling of thermal processes in microcontroller system is addressed. The proposed models allow to describe thermal processes during work of an evaluation system. The temperature in critical places of the system is measured using thermal camera. The proposed models have the form of hybrid transfer functions, containing both Integer Order (IO) and Fractional Order (FO) parts. The step responses of the proposed transfer functions are computed analytically. Results of experiments show that the proposed models are more accurate in the sense of Mean Square Error (MSE) cost function than typical transfer function models with delay. The proposed models can be applied to predict of overheating of microcotroller systems. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023.

关键词： Microcontrollers

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