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Efficient Real-Time Face Recognition-Based Attendance System with Deep Learning Algorithms 2

Efficient Real-Time Face Recognition-Based Attendance System...

引用

2nd IEEE international conference on Intelligent and Innovative Technologies in Computing, Electrical and Electronics, ICIITCEE 2024

作者： Painuly, Kritagya Bisht, Yukti Vaidya, Himadri Kapruwan, Akanksha Gupta, Rupesh Computer Science and Engineering Graphic Era Hill University Uttarakhand Dehradun India Computer Science and Engineering Graphic Era Deemed to Be University Uttarakhand Dehradun India Computer Science and Engineering Chitkara University Punjab India

ISBN: (纸本)9798350306415

Efficient Real-Time Face recognition-based attendance systems with deep learning algorithms strive for precise and real-time performance in managing attendance across various institutions. This solution outlines key targets as well as robust face detection, model selection, real-time processing, information collection, and ensuring accuracy and reliability in face recognition by combining dlib, cvzone, and YOLO algorithms for face detection, and blur detection to improve the system's efficiency. In a nutshell, the suggested system offers a promising approach to attendance control in challenging situations by using advanced methods to signify high accuracy, real-time processing, and value. © 2024 IEEE.

关键词： CNNs computer Vision Deep learning YOLO

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Smart System to Detect under Loading and Overloading of Wagons in Transportation

Smart System to Detect under Loading and Overloading of Wago...

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2024 international conference on Smart Systems for Electrical, Electronics, Communication and computer Engineering, ICSSEEC 2024

作者： Kowsalya, M. Kalaimathi, B. Alamelu Alias Rajasree, S. Kumar, A. Naresh Prabhakaran, M. Nishanth Gokul, M. Nitheesh Sri Ramakrishna Engineering College Department of ECE Tamilnadu India Sri Ramakrishna Engineering College Department of ECE Coimbatore India

ISBN: (纸本)9798350378177

The transportation industry is currently facing a significant challenge with overloading, which not only poses safety risks but also leads to higher operational costs. One potential solution involves the implementation of advanced technology, such as sophisticated weighing systems and control units based on Raspberry Pi Pico, directly within the containers. These integrated systems enable real-time tracking of cargo weight and location, providing essential data to stakeholders. Additionally, the incorporation of GSM modules and Wi-Fi module enhances security measures by promptly alerting authorities to instances of overloading or theft through web dashboard. These advancements in technology aim to create a transportation environment characterized by increased safety, operational efficiency, and reliability. © 2024 IEEE.

关键词： Cargo Weights control units GSM modules Security alerts Weighting systems

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Master-Slave Iterative Learning control on EtherCAT-based Selective Laser Melting System 6

Master-Slave Iterative Learning Control on EtherCAT-based Se...

引用

6th international conference on control and Robotics, ICCR 2024

作者： Huang, Ruei-Yu Chen, Yen-Jen Cheng, Chung-Wei Lee, An-Chen Tung University Mechanical Engineering National Yang Ming Chiao Hsinchu Taiwan

ISBN: (纸本)9798331518158

This study addresses the synchronization and performance issues of the scanning system and the power system in an EtherCAT-based selective laser melting (SLM) system, which are critical for improving the quality and reliability of the manufacturing process. In response to these challenges, we propose a master-slave iterative learning control architecture. By handling the position loops of the scanning and power systems on a master computer and applying advanced control methods, including disturbance observers, robust feedback controllers, and feedforward controllers, we aimed to enhance system performance. Additionally, learning controllers were used to further reduce repetitive tracking and contour errors. In the experiments, we compared three methods: the traditional distributed control, the proposed hybrid servo control, and the proposed hybrid learning control. Compared to the traditional distributed control, experiments demonstrated that the proposed hybrid servo control architecture improved tracking errors in the scanning system by 15% and contour errors by 12%, with a 63% reduction in tracking errors for the power system. Moreover, the proposed hybrid learning control improved tracking errors in the scanning system by 28% and contour errors by 20%, with an 87% reduction in tracking errors for the power system. These results highlight the effectiveness of the architecture in enhancing SLM process quality and reliability, showing great potential for broader applications in advanced manufacturing. © 2024 IEEE.

关键词： Selective laser melting

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Fall Detection Algorithm Based on Improved Yolov7

Fall Detection Algorithm Based on Improved Yolov7

引用

2024 international conference on Mechatronics and Intelligent control, ICMIC 2024

作者： Cao, Hu Xu, Jie School of Computer Science Jiangsu University of Science and Technology Zhenjiang China

ISBN: (数字)9781510686847

ISBN: (纸本)9781510686830

Aiming at the problems of slow detection speed and low accuracy in current human fall detection tasks, a fall detection algorithm based on Yolov7 was proposed. ODConv-ELAN module was constructed in Yolov7 backbone network to replace the original ELAN structure and enhance the ability of extracting target features. Secondly, the more advanced EIoU function is used as the new boundary frame loss function, which improves the convergence speed and efficiency of the prediction frame in the process of model training. Finally, CA attention mechanism is introduced into the output terminal of the network to improve the detection performance of human fall behavior. In addition, a fall detection data set in the campus environment was created. The accuracy P of the improved algorithm in this data set reached 94.34%, the recall rate R reached 92.34%, and the average accuracy mAP reached 94.65%, which realized the demand for more accurate human fall detection. © 2025 SPIE.

关键词： Fall detection

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Advance Facial Analysis: A Hybrid Approach with CNNs, SVMs, and Random Forest for Age and Gender Estimation

Advance Facial Analysis: A Hybrid Approach with CNNs, SVMs, ...

引用

2024 international conference on Computational Intelligence and Computing Applications, ICCICA 2024

作者： Singh, Kulvinder Singh, Balkar Sunrise University Department Of Computer Science & Engineering Rajasthan Alwar India

ISBN: (纸本)9798350306446

In an era marked by the widespread adoption of Artificial Intelligence (AI) and advanced computer vision technologies, the analysis of facial attributes has become increasingly important across various domains such as access control, video surveillance, and personalized services. A single facial image contains a wealth of demographic information including age, gender, race, and emotional expression. The paper focuses on a unique approach for facial image analysis that combines Convolutional Neural Networks (CNNs) for detailed feature extraction, traditional models like Support Vector Machine for age prediction, and Random Forest also for gender classification. The proposed approach not only addresses existing limitations but also enhances predictive accuracy. The effectiveness of our method was extensively evaluated using the Adience Benchmark dataset, producing outstanding results in both age prediction and gender classification tasks. Through thorough assessments across multiple datasets and evaluation techniques, the proposed solution showcases improved performance as compared to current state of the art methods, affirming its efficacy and reliability. © 2024 IEEE.

关键词： Access control

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Methodology for Multi-Domain Coupling Modeling of Unmanned Surface Vehicle Dynamics Based on Modelica 8

Methodology for Multi-Domain Coupling Modeling of Unmanned S...

引用

8th international conference on Electrical, Mechanical and computer Engineering, ICEMCE 2024

作者： Zhang, Haodong Mou, Jianhui Li, Junjie Liang, Dedong Yantai University College of Information Engineering Shandong Yantai264000 China Suzhou Tongyuan Software and Control Technology Co. Ltd Jiangsu Suzhou215000 China

ISBN: (纸本)9798331506230

The widespread deployment of Unmanned Surface Vehicles (USVs) in military reconnaissance and oceanic exploration has underscored the need for sophisticated modeling and simulation technologies. Current studies primarily focus on simulations of individual systems, which often encounter difficulties with model integration and lack efficiency. This research utilizes the Modelica language and the MWorks platform to develop an advanced multi-domain modeling and simulation framework for USVs. This framework constructs an integrated model that includes the dynamics, control, power, transmission, and waterjet propulsion systems. The simulations, encompassing scenarios such as straight navigation, rotational maneuvers, reverse movements, and task-specific actions, highlight the model's ability to adapt dynamically to complex marine environments. The efficacy of this model enhances USV design and autonomous operations, facilitating path planning and real-time obstacle avoidance, and sets the stage for further studies on collective control strategies. © 2024 IEEE.

关键词： Unmanned surface vehicles

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Effortless Meeting Analysis Automation 15

Effortless Meeting Analysis Automation

引用

15th international conference on Advances in Computing, control, and Telecommunication Technologies, ACT 2024

作者： Mohit, Harsh Chaitanya, K. Kumar, Maneesh Kushal, B. Shanthakumara, A.H. Department of Computer Science and Engineering Siddaganga Institute of Technology Tumakuru India

ISBN: (纸本)9798331300579

The "Automated DSM Insight Analyzer" is a groundbreaking initiative that revolutionizes the analysis of Daily Stand-Up Meetings (DSMs). Leveraging a sophisticated combination of cutting-edge technologies, including a Flask-based API for audio processing, Azure Speech-to-Text for precise transcription, and the GPT API for advanced Natural Language Processing (NLP), this solution provides comprehensive insights. It addresses challenges in resource management and bug tracking, ensuring the prompt generation of actionable insights. With multilingual support and seamless integration with Google Calendars, it enhances productivity, offering a user-friendly platform that fosters improved collaboration and project success through the extraction of valuable insights from daily meetings. © Grenze Scientific Society, 2024.

关键词： Application programming interfaces (API)

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Performance Evaluation of a ROS2 Based Automated Driving System 10

Performance Evaluation of a ROS2 Based Automated Driving Sys...

引用

10th international conference on Vehicle Technology and Intelligent Transport Systems, VEHITS 2024

作者： Kouril, Jorin Schaüfele, Bernd Radusch, Ilja Schnor, Bettina Berlin Germany Berlin Germany Department of Computer Science University of Potsdam Potsdam Germany

ISBN: (纸本)9789897587030

Automated driving is currently a prominent area of scientific work. In the future, highly automated driving and new advanced Driver Assistance Systems will become reality. While advanced Driver Assistance Systems and automated driving functions for certain domains are already commercially available, ubiquitous automated driving in complex scenarios remains a subject of ongoing research. Contrarily to single-purpose Electronic control Units, the software for automated driving is often executed on high performance PCs. The Robot Operating System 2 (ROS2) is commonly used to connect components in an automated driving system. Due to the time critical nature of automated driving systems, the performance of the framework is especially important. In this paper, a thorough performance evaluation of ROS2 is conducted, both in terms of timeliness and error rate. The results show that ROS2 is a suitable framework for automated driving systems. Copyright © 2024 by SCITEPRESS - Science and Technology Publications, Lda.

关键词： advanced driver assistance systems

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RIS-assisted multi-user visible light communication in IIoT scenarios: prototype design and feasibility study 6

RIS-assisted multi-user visible light communication in IIoT ...

引用

6th international conference on Optoelectronic Science and Materials, ICOSM 2024

作者： Ye, Ziwei Li, Dun Zhang, Erfeng Zhu, Yijun Information Engineering University Henan Province Zhengzhou450000 China

ISBN: (数字)9781510686823

ISBN: (纸本)9781510686816

As the multi-user wireless communications in Industrial Internet of Things (IIoT) scenarios are increasingly demanded, conventional visible light communication (VLC) solutions suffer from the problems such as the inter-cell crosstalk and the latency when switching the cells. The introduction of reconfigurable intelligent surface (RIS) supplies new approach of reconfigurable optical cells based on digital holography. This paper proposes the prototype model of the holography-based multi-user VLC system. The computer-generated holograms (CGH) generation quality is analyzed, and the lens system to adjust the positions and the sizes of the generated cells is designed. The feasibility of the system is verified by simulation, which shows that the method can support 5 users data transmission. © 2024 SPIE.

关键词： computer generated holography

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Enhancing Network Security: A Comparative Analysis of Deep Learning and Machine Learning Models for Intrusion Detection

Enhancing Network Security: A Comparative Analysis of Deep L...

引用

2024 international conference on E-Mobility, Power control and Smart Systems, ICEMPS 2024

作者： Ajeesh, Arunima Mathew, Tessy Mar Baselios College of Engineering and Technology Department of Computer Science and Engineering Thiruvananthapuram India

ISBN: (纸本)9798350394399

The escalating reliance of computer networks on security systems exposes them to increasing threats. In response, an advanced security system is proposed, utilizing machine learning and deep learning techniques and leveraging the NSLKDD and CSE-CIC-IDS2018 datasets. Addressing the class imbalance challenges, the DSSTE algorithm is adopted to optimize model performance. Evaluation involves six, machine learning and deep learning methods: XGBoost, LSTM, Bi-LSTM, CNN, and VGG19, with a focus on assessing speed, false positive rate and detection efficiency. Experimental results underscore DSSTE's efficacy in mitigating class imbalance and enhancing overall intrusion detection. The proposed IDS, empowered by machine learning and DSSTE, ensures early detection and strengthens network security by countering intrusion attempts. Performance is compared with systems utilizing SMOTE and ADAASYN for data balancing. © 2024 IEEE.

关键词： Intrusion detection

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