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检索条件"机构=Computer Engineering and Informatics"

共 20318 条记录，以下是1131-1140 订阅

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CNN Architectures for Vehicle Detection in V2X Environments: A Comparative Study

CNN Architectures for Vehicle Detection in V2X Environments:...

引用

IEEE Conference on Standards for Communications and Networking (CSCN)

作者： Vasileios Efthymiou Stylianos Basagiannis Sophia Petridou Department of Applied Informatics University of Macedonia Greece Department of Computer Informatics & Telecommunications Engineering International Hellenic University Greece

ISBN: (数字)9798331507428

ISBN: (纸本)9798331507435

Leveraging convolutional neural networks (CNNs) to Vehicle-to-Everything (V2X) communication systems offers a promising approach to vehicle detection, which is essential for improving road safety and traffic efficiency. At the same time, parameterization of CNNs’ architectures in order to achieve high accuracy in moving objects’ detection becomes an engineering challenge, especially when data pre- and post-processing solutions need to respect timing requirements. Our study evaluates the performance of five CNN architectures, namely YOLO in v5, v8, and v9, Faster R-CNN, and VGG16, for car detection. We utilize an open dataset including images derived from road-traffic environments and assess the models’ performance using benchmark evaluation metrics, i.e., precision, recall, mean Average Precision (mAP50, mAP50 – 95), and F1-score. Furthermore, we analyze their computational requirements, in terms of execution time and resource demands, which are critical factors when considering real-time applications in V2X systems, such as autonomous driving and traffic management. Our evaluation results indicate that, while the YOLO architecture exhibits the best balance of speed and accuracy, Faster R-CNN has higher detection performance at the cost of greater computational demand. This paper provides insights into each model’s strengths and limitations offering guidance for selecting optimal architectures tailored to V2X-related applications.

关键词： YOLO Accuracy Vehicle detection Computational modeling computer architecture Road safety Timing Convolutional neural networks Vehicle-to-everything Standards

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Enhancing the Recommender System Algorithm's Quality Through the Utilization of Affinity Analysis 16

Enhancing the Recommender System Algorithm's Quality Through...

引用

16th IEEE International Scientific and Technical Conference Actual Problems of Electronic Instrument engineering, APEIE 2023

作者： Stubarev, Igor M. Alsova, Olga K. Yakimenko, Alexander A. Novosibirsk State Technical University Faculty of Automation and Computer Engineering FB Consult Novosibirsk Russia Novosibirsk State Technical University Faculty of Automation and Computer Engineering Novosibirsk Russia Novosibirsk State Technical University Faculty of Automation and Computer Engineering Institute of Computational Mathematics and Mathematical Geophysics SB RAS Laboratory of Geophysical Informatics Novosibirsk Russia

ISBN: (纸本)9798350330885

The demand for auxiliary systems that utilize methods and technologies of intellectual data analysis and machine learning is increasing in the CRM system development field. These systems are capable of generating valuable insights from vast amounts of data collected in CRM. The article shows the results of the development and study of the CRM system using the methods of affinity analysis. Earlier, the authors developed and implemented the base version of the recommender algorithm based on the use of cluster data analysis and collaborative filtration [1, 2]. The new version of the algorithm additionally uses affinity analysis methods to form recommendations for the selection of products, which made it possible to increase the accuracy of the recommendation system (service) by metrics F2 on average from 67.98% to 81.24% with an increase in the time for issuing recommendations (On average by 2.47 ms). The study and comparison of the basic and modified versions of the algorithm were executed using data sourced from insurance companies, furnished by "FB Consult". © 2023 IEEE.

关键词： Collaborative filtering

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Editorial

引用

Computational Geometry: Theory and Applications 2024年 122卷

作者： Bae, Sang Won Okamato, Yoshio Division of Artificial Intelligence and Computer Science Kyonggi University Korea Republic of Department of Computer and Network Engineering Graduate School of Informatics and Engineering The University of Electro-Communications Japan

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Recognition of Dog Motion States: Ensemble vs Deep Learning Models

Recognition of Dog Motion States: Ensemble vs Deep Learning ...

引用

International Conference on Information, Intelligence, Systems and Applications (IISA)

作者： George Davoulos Iro Lalakou Ioannis Hatzilygeroudis Computer Engineering and Informatics Department University of Patras Patras Greece Department of Informatics and Telecommunications University of Peloponnese Tripolis Greece

ISBN: (数字)9798350368833

ISBN: (纸本)9798350368840

Dog activities recognition, especially dog motion status recognition, is an active research area. Although several machine learning and deep learning approaches have been used for dog motion states recognition, use of ensemble learning methods is rather missing as well as a comparison with deep learning ones. This paper focuses on the use of ensemble classifiers and deep learning neural networks in recognizing dog motion states, and their comparison. Our results show a slight superiority in accuracy (94.7 % vs 92.8%) of deep learning, which is quite comparable to the state-of-the-art, but at the cost of larger complexity and training time, which makes ensemble techniques still attractive.

关键词： Deep learning Training Machine learning algorithms Computational modeling Stacking Neural networks Dogs Time measurement Gyroscopes Motion measurement

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Handwritten Signature Recognition Using Siamese Neural Network

Handwritten Signature Recognition Using Siamese Neural Netwo...

引用

International Conference on computer engineering, Network and Intelligent Multimedia (CENIM)

作者： Yuliana Setiowati Arna Fariza Muhamad Rifqi Luthfi Ramadhan Informatics and Computer Engineering Department Politeknik Elektronika Negeri Surabaya Surabaya Indonesia

ISBN: (数字)9798350368802

ISBN: (纸本)9798350368819

This research proposes a novel approach to addressing the issue of signature authenticity identification by implementing Deep Metric Learning (DML). The aim of this study is to develop a DML model with high accuracy in training and testing processes that can be integrated with a mobile application for signature authenticity verification. The data used in this research are signature images from 90 individuals, divided into two categories: genuine signatures and forged signatures. Testing results show that the developed model has an accuracy of 85.7 % , with high precision for the forged signature class at 95.9% and recall for the genuine signature class at 94.9%. The conclusion of this research is that the developed DML model is reliable for signature verification, although further development is needed to improve the model's performance, especially in detecting forged signatures. Suggestions for future research include increasing the amount and variety of training data, integrating the model with a mobile application, and testing the model under various conditions and on different devices.

关键词： Training Handwriting recognition Solid modeling Accuracy Neural networks Training data Solids Data models Mobile applications Testing

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Secure & Traceable Companies File Management System Using Blockchain and IPFS

Secure & Traceable Companies File Management System Using Bl...

引用

IEEE International Symposium on Consumer Electronics (ISCE)

作者： Cahyo Arissabarno Sritrusta Sukaridhoto Idris Winarno Department of Informatics and Computer Engineering Politeknik Elektronika Negeri Surabaya Surabaya Indonesia

ISBN: (数字)9798350365191

ISBN: (纸本)9798350365207

With the advancement of cloud-based file management platforms, sharing and storing files in the company's area can be easily achieved through a variety of file-sharing platforms. However, these platforms often lack of security and adequate access logs or activity records for the shared files, resulting in a lack of control and traceability for users. This research proposes an traceable and secure system for managing files in companies using blockchain and IPFS. The content ID of uploaded files to IPFS will be stored on the blockchain along with user access rights and access logs. Integration with the existing company file management system is also facilitated by the use of the change data capture method. Experimental findings demonstrate that the system offers the desired traceability of access and activity while also meeting data security requirements such as confidentiality, integrity, and availability. Furthermore, performance tests indicate satisfactory outcomes with 0.8 seconds per MB for file storage on IPFS, and 4.1 seconds per transaction for data storage on Blockchain. The experimental results revealed that the proposed system, integrating blockchain and IPFS, successfully addressed the need for traceability of access and activity for the company's data, providing a significant improvement in data security and management over existing solutions.

关键词： Data security Memory Companies Permission Blockchains

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Income Forecasting for Multi-Category Product using ARIMA Approach

Income Forecasting for Multi-Category Product using ARIMA Ap...

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International Seminar on Research of Information Technology and Intelligent Systems (ISRITI)

作者： Rizki Elisa Nalawati Asep Taufik Muharram Bambang Warsuta Ayres Pradiptyas Gresia Andayani Mauldy Laya Dept. of Informatics and Computer Engineering Politeknik Negeri Jakarta Depok Indonesia

ISBN: (数字)9798331519643

ISBN: (纸本)9798331519650

The rapid development of e-commerce platforms has brought significant changes in consumer behavior and business marketing strategies. In facing increasingly tight competition, some online stores need to predict revenue for the products they have. However, most online stores have more than one category, so it is necessary to evaluate predictions for each category. This problem can be handled by implementing Autoregressive Integrated Moving Average (ARIMA). This approach can be used to handle non-stationarity by having "integrated" components become stationary through differencing. The average MAPE value of all categories of cosmetic products is 12.144%. The development of this prediction system is in accordance with the stages in CRISP-DM. This approach provides a structured framework for carrying out data mining projects with six clear phases.

关键词： Seminars Consumer behavior Electronic commerce Data mining Intelligent systems Information technology Forecasting Business

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IT-Security Risk Based Approach for Secure Operation of Distributed Data Platforms in Supply Chains

IT-Security Risk Based Approach for Secure Operation of Dist...

引用

2024 IEEE International Conference on Industrial engineering and engineering Management, IEEM 2024

作者： Voß, Marvin Kallisch, Jonas Runge, Maxim Theus, Tobias Niemann, Karl-Heinz Wunck, Christoph Faculty I - Electrical Engineering and Information Technology University of Applied Sciences and Arts Hannover Germany Department of Engineering Section Electrical Engineering and Computer Science University of Applied Sciences Leer Emden Germany Faculty of Mathematics Informatics and Statistics Ludwig Maximilian University Munich Germany

ISBN: (纸本)9798350386097

This paper presents the development of a secure data platform designed to enhance operational efficiency and to facilitate cross-company collaboration within the manufacturing supply chain. The platform is designed to ease secure information exchange while maintaining the sovereignty of each participant, leveraging standardized security features and advanced technologies such as federated learning. Security measures are based on a comprehensive risk analysis, which methodically identifies, assesses, and mitigates potential threats. Moreover, federated learning models that are not transparent are utilized. This allows data owners to maintain control over sensitive information within the consortium. The described approach markedly enhances both security and operational collaboration across the industry, representing a crucial stride towards more integrated and efficient supply chain management in manufacturing. © 2024 IEEE.

关键词： Risk analysis

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Deep-Source EEG Generation with Deep Learning from Different Configurations of Surface EEG

Deep-Source EEG Generation with Deep Learning from Different...

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IEEE International Conference on Consumer Electronics (ICCE)

作者： Jiadao Zou Qingxue Zhang Luddy School of Informatics Computing and Engineering Indiana University Department of Computer Science and Department of Biomedical Engineering Indiana University School of Informatics Computing and Engineering Indiana University Luddy Indianapolis

ISBN: (数字)9798331521165

ISBN: (纸本)9798331521172

Brain dynamics big data is of increasing promise for many applications like epilepsy detection and cognitive understanding, with the advancements of consumer technology. However, the deep-source brain measurement is difficult. In this study, we target the brain electroencephalogram (EEG) application, and investigate the deep-source EEG generation from surface EEG towards convenient big data. The deep learning algorithm has been developed to mine different configurations of the surface EEG streams, including the single-channel and multi-channel cases, for deep-source EEG generation. Promising experiments on the epilepsy application have been conducted, demonstrating the great promise of deep-learning-empowered deep-source EEG generation. This study will greatly advance brain dynamics mining towards smart consumer technology.

关键词： Deep learning Heuristic algorithms Smart healthcare Epilepsy Big Data Electroencephalography Streams Consumer electronics

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A Cloud-Based Key Rolling Technique for Alleviating Join Procedure Replay Attacks in LoRaWAN-based Wireless Sensor Networks

A Cloud-Based Key Rolling Technique for Alleviating Join Pro...

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2024 IEEE International Conference on Big Data, BigData 2024

作者： Papatsaroucha, Dimitra Astyrakakis, Nikolaos Pallis, Evangelos Grammatikis, Panagiotis I. Radoglou Sarigiannidis, Panagiotis G. Markakis, Evangelos K. Hellenic Mediterranean University Department of Computer & Electrical Engineering Heraklion Greece University of West Attica Department of Industrial Design and Production Engineering Athens Greece K3Y Sofia Bulgaria University of Western Macedonia Department of Informatics and Telecommunication Engineering Kozani Greece

ISBN: (纸本)9798350362480

Nowadays, numerous devices are utilizing the IoT world, connecting and providing access to data and sensor measurements in vast networks of interconnected objects and devices. Considering the great communication distances that need to be covered occasionally, the LoRaWAN network was proposed as it employs Low Power (LP) and Long Range (LoRa) protocols that reduce device energy consumption while maximizing communication range. A gateway to the cloud authenticates LoRaWAN IoT devices before data transmission. This procedure begins with an unencrypted Join Request. A Join Request includes, among others, a Message Integrity Code (MIC), which is the result of encrypting the unencrypted contents of the message using an AppKey that is securely stored both in the cloud and the IoT device. However, malicious actors acting as Man-In-the-Middle (MITM) can interfere in the communication channel, reverse engineer the MIC value, and derive the AppKey. They can then initiate a Join Request that is misinterpreted as coming from a legitimate device and gain access to the communication channel. This paper introduces a novel approach that focuses on the continuous regeneration of the AppKey, necessitating frequent re-joining and re-authentication of IoT devices within the network. The suggested method, which can be added as an extra layer of security in LoRaWAN networks, uses a key rolling technique similar to the one used in automobile central locking systems, and is developed as an optimised and scalable microservice for various LoRaWAN installations and versions. Through the evaluation process, significant findings emerged, demonstrating the effectiveness of the proposed security solution in mitigating replay attacks. The system successfully prevented the server from getting flooded by malicious packets, distinguishing it from a system lacking the proposed mechanism. Remarkably, this accomplishment was made without causing any noticeable delay to the communication process. In addit

关键词： Network security

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