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检索条件"任意字段=9th IEEE International Conference on Engineering of Complex Computer Systems"

共 16756 条记录，以下是11-20 订阅

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Security and Privacy of Artificial Intelligence with Ethical Concerns 9

Security and Privacy of Artificial Intelligence with Ethical...

引用

9th ieee international conference on Data Science in Cyberspace, DSC 2024

作者： Li, Yihong University of Toronto Department of Electrical and Computer Engineering Canada

ISBN: (纸本)9798350391367

In recent years, artificial intelligence has entered the public eye across various fields, enhancing productivity and increasing social welfare. However, it has also raised significant security and privacy concerns due to the ethical uncertainties associated with this technology, requiring researchers to establish and refine the rules. this paper aims to categorize the security and privacy issues brought by AI and their relation to social ethics, analyze this complex topic from technical, social, and legal perspectives, and propose the current optimal solutions while predicting future developments. © 2024 ieee.

关键词： Differential privacy

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Research On the Key Frame Selection Method Of YOLOv5-Based Intelligent Damage Determination System 9

Research On The Key Frame Selection Method Of YOLOv5-Based I...

引用

9th international conference on Automation, Control and Robotics engineering (CACRE)

作者： Zhu, Qianqian Liu, Yingnan Wu, Xuening Huang, Jiaying China Automot Technol & Res Ctr Co Ltd Automot Data China Co Ltd Tianjin Peoples R China

ISBN: (纸本)9798350350319;9798350350302

In vehicle damage claims, the intelligent damage determination method based on computer vision instead of manual observation has become the future direction of technology. In the process of wise damage determination, because of the difficulty that the images taken manually cannot be quickly shot with the image quality applicable to the system, this paper proposes a keyframe selection method based on the YOLOv5 model, which solves the problems of convenience and ease of use of the intelligent damage determination system by adding the real-time operation guidance function at the time of the shooting. Firstly, the mobile real-time detection model YOLOv5 detects and counts the vehicle appearance parts. Secondly, the underlying logic determination model guides the user to complete the shooting distance adjustment. Experimenting with the self-built vehicle image data set, the average accuracy of mAP50 reached 94.1%, and YOLOv5 can meet the requirements of real-time and accuracy of keyframe selection in shooting environments such as uneven lighting and complex surrounding background.

关键词： YOLOv5 Deep Learning computer Vision

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Big Data Analytics in loT Challenges and Opportunities 9

Big Data Analytics in loT Challenges and Opportunities

引用

9th international conference on Science, Technology, engineering and Mathematics, ICONSTEM 2024

作者： Kirubakaran, S. Vidhya, R. Prlya, V. Kalai ShyamPrakash, D. Dhotre, Sunita Balaji, N. Alangudi Cmr College of Engineering And Technology Department of Computer Science And Engineering Telangana Hyderabad501401 India Sri Krishna College of Technology Department of Computer Science And Engineering Tamil Nadu Coimbatore641042 India Rmk College of Engineering And Technology Department of Computer Science And Engineering Puduvoyal601206 India Sri Eshwar College of Engineering Deportmem of Computer Science And Business Systems Tamil Nadu Coimbatore641202 India College of Engineering Department of Computer Engineering Maharashtra Pune411043 India KoneruLakshmaiah Education Foundation Department of Computer Science And Engineering Andhra Pradesh Vaddeswaram522302 India

ISBN: (纸本)9798350365092

the intricate interplay between Big Data analytics and the Internet of effects is explored in this paper. the focus of this exploration is the integration of Big Data analytics into Internet of effects surroundings, probing into the complex geography and examining both the advantages and disadvantages. In the current period, where Internet of effects(loT) bias induce unknown quantities of data, the investigates the challenges associated with the collection and analysis of massive datasets. issues are under consideration, including data security, sequestration, scalability, and real-time processing. Again, openings lie in gaining pivotal perceptivity, enhancing decision- making processes, and fostering invention. this exploration provides a comprehensive understanding of the commerce between Big Data analytics and the Internet of effects(IoT), offering a precious resource for companies, academic institutions, and government officers seeking to navigate and acclimatize to this fleetly expanding confluence of technologies. © 2024 ieee.

关键词： Scalability

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GNF: Generative Natural Faces Dataset for Face Expression Recognition Task 9

GNF: Generative Natural Faces Dataset for Face Expression Re...

引用

9th international conference on computer Science and engineering, UBMK 2024

作者： Özer, Cansu Daǧli, Volkan Gürkan, Mustafa Kaǧan International R&d Orion Innovation Turkey Istanbul Turkey Bahcesehir University Istanbul Turkey

ISBN: (纸本)9798350365887

In computer vision, Facial Expression Recognition (FER) is a critical task in various applications, such as human-computer interaction. the effectiveness of FER systems depends mainly on the quality and diversity of the datasets used. the traditional FER data sets may not fully satisfy these requirements due to the lack of diversity, class imbalance, and mislabeling. To address some of these issues, we introduce a novel facial expression dataset created by using Generative Adversarial Networks (GANs). To evaluate its efficacy, the training and test capabilities of the dataset on various CNN architectures are compared with benchmark FER datasets. © 2024 ieee.

关键词： Generative adversarial networks

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Application of Genetics Algorithms in Cryptography 28

Application of Genetics Algorithms in Cryptography

引用

28th ieee international conference on Intelligent engineering systems (INES)

作者： Pekarcik, Peter Chovancova, Eva Chovanec, Martin Stancel, Martin Tech Univ Kosiciach Fak Elektrotechn Informat Katedra Pocitacov Informat Letna 9 Kosice 04200 Slovakia

ISBN: (纸本)9798350367607;9798350367591

One of the most essential subfields of modern IT is undoubtedly cybersecurity. the cybersecurity practice, also known as cryptology, combines various disciplines like computer science, computer engineering, and mathematics to create complex algorithms. In our work, we combine cryptology with the field of genetics algorithms to develop new encryption algorithms. Firstly, we introduced the fundamental theories of these two fields. It aims to teach basic knowledge of using genetic algorithms to select specific parts of encryption algorithms (chromosomes) and combine them to produce new encryption algorithms (offspring). the standard flow of the genetic algorithm is divided into the initial population's creation process, evaluation, fitness score assignments, selection, crossover, and mutation. We will take a deeper look at the process of assignments of fitness score and crossover. these processes ' new design, implementation, and testing allow us to reach the results presented.

关键词： crossover cryptography decryption decryption algorithms encryption encryption algorithms fitness score genetic algorithms initial population mutation selection

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Enhancing Cyberbullying Detection in Social Media: Leveraging Ontology with Skip- Gram Optimization 9

Enhancing Cyberbullying Detection in Social Media: Leveragin...

引用

9th international conference on Communication and Electronics systems, ICCES 2024

作者： Sathya, J. Fernandez, F. Mary Harin Saveetha School of Engineering Saveetha Institute of Medical And Technical Sciences Saveetha University Department of Computer Science and Engineering Chennai India

ISBN: (纸本)9798350377972

the pervasive issue of cyberbullying on social media platforms highlights the critical need for robust detection systems to ensure user safety. this research introduces a novel approach to enhance cyberbullying identification by integrating ontology with the Skip-gram optimization technique. the proposed methodology leverages ontological frameworks to identify semantic relationships within social media content, combined with Skip-gram optimization to generate accurate and robust word embeddings. the objective is to improve both the precision and effectiveness of cyberbullying detection. Ontology-enhanced embeddings demonstrate superior performance compared to standard word embeddings when used with an LSTM classifier, as indicated by experimental results. the findings show significant improvements in detecting instances of cyberbullying across various social media platforms. In the rapidly evolving digital landscape, the combination of ontology and Skip-gram optimization offers a promising solution to the complex challenges of cyberbullying detection. © 2024 ieee.

关键词： Anonymity

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Enhancing Medical Image Analysis: Leveraging Transfer Learning in Convolutional Neural Networks for Tuberculosis Detection 9

Enhancing Medical Image Analysis: Leveraging Transfer Learni...

引用

9th ieee international conference for Convergence in Technology, I2CT 2024

作者： Dahiwadkar, Piyush Pankaj Bhamre, Hrishin Mandar Sahitya, Aarti Dept. of Computer Engineering Mumbai India

ISBN: (纸本)9798350394474

Advancements in medical imaging have paved the way for image-based computer-aided diagnosis (CADx) systems, revolutionizing the detection of lung abnormalities, including lung nodules and diffuse lung diseases. this paper explores the potential of convolutional neural networks (CNNs) in image-based CADx without the reliance on image-feature extraction, presenting a powerful alternative to feature-based CADx methods. Additionally, we introduce an image-based computer-aided detection (CADe) algorithm employing regions with CNN features (R-CNN) for precise identification of lung abnormalities. We conduct comprehensive evaluations of our image-based CADx utilizing CNN and CADe employing R-CNN, demonstrating their effectiveness across various lung abnormalities. © 2024 ieee.

关键词： computer aided diagnosis

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Textual Analysis and Computational Insights into Alisher Navoi's 'Divan of the AqQoyunlu Admirers' 9

Textual Analysis and Computational Insights into Alisher Nav...

引用

9th international conference on Science, Technology, engineering and Mathematics, ICONSTEM 2024

作者： Sultanov, Tulkin Ablakulova, Iroda Halimova, Nilufar Husanova, Dildora Ananth, Christo Kumar, T. Ananth 'Silk Road' International University of Tourism And Cultural Heritage Samarkand Uzbekistan Samarkand State University Uzbekistan Ifet College of Engineering Computer Science And Engineering Tamilnadu India

this abstract analyzes Alisher Navoi9;s 9;Divan of the AqQoyunlu Admirers9; using computational methods. this investigation uses computer science methods to gain deeper insights and nuanced perspectives from ... 详细信息

ISBN: (纸本)9798350365092

this abstract analyzes Alisher Navoi's 'Divan of the AqQoyunlu Admirers' using computational methods. this investigation uses computer science methods to gain deeper insights and nuanced perspectives from Navoi's complex poetry collections. this research project uses text mining, natural language processing, and computational analysis to identify Navoi's poetry's themes, linguistic patterns, and stylistic elements. Computational tools enable a thorough text analysis, which makes it easier to study Navoi's artistic expression, rhetorical devices, and cultural nuances in the 'Divan.' this study seeks to reveal Navoi's poetic verses' hidden connections, recurring motifs, and thematic variations. Algorithms will parse, categorize, and interpret text. It also examines how historical and cultural contexts have shaped poetry. A computational lens will be used to understand the socio-cultural background of the AqQoyunlu period. this investigation used computational analysis to supplement traditional literary analysis by providing quantifiable and structured insights into Navoi's work. this research combines computer science and literature to help readers understand Alisher Navoi's 'Divan of the AqQoyunlu Admirers'. © 2024 ieee.

关键词： Natural language processing systems

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AI-Enhanced Intelligent Control systems for Electric Vehicles 9

AI-Enhanced Intelligent Control Systems for Electric Vehicle...

引用

9th international conference on Science, Technology, engineering and Mathematics, ICONSTEM 2024

作者： Tagesse, Tamirat Arulkumar, S. Saravanan, A. Vibhakar, Chirag Shobana, D. Chokkalingam, Arun Wachemo University Department of Electrical And Computer Engineering Ethiopia S.A Engineering College Department of Master of Business Administration Chennai Tamil Nadu Thiruverkadu600077 India Department of Electrical Engineering Gujarat Power Engineering &. Research Institute Mevad - Mehsana Gujarat Technological University Gujarat Ahmedabad382710 India Panimalar Engineering College Department of Electrical And Electronics Engineering Tamil Nadu Chennai600125 India R.M.K. College of Engineering And Technology Department of Electronics And Communication Engineering Tamil Nadu Puduvoyal601206 India

ISBN: (纸本)9798350365092

A comprehensive overview of the operation of artificial intelligence(AI) in enhancing intelligent control systems for electric vehicles(EVs). As the automotive assiduity transitions towards electrification, the development of advanced control systems becomes decreasingly pivotal to optimize the performance, effectiveness, and safety of EVs. AI ways, including machine literacy, deep literacy, and underpinning literacy, offer promising results to address the complex dynamics and misgivings essential in EV operation. this review explores the integration of AI algorithms into colorful aspects of EV control systems, similar as powertrain operation, battery operation, energy operation, and vehicle autonomy. Case studies and experimental results are presented to demonstrate the effectiveness and benefits of AI- enhanced control systems in perfecting EV performance, extending battery life, and enhancing overall driving experience. likewise, challenges, openings, and unborn directions for exploration and development in this field are bandied to pave the way for the wide relinquishment of AI- driven intelligent control systems in the EV assiduity. © 2024 ieee.

关键词： Control theory

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AI-Driven Retention: A Hybrid Approach to Employee Turnover Prediction 9

AI-Driven Retention: A Hybrid Approach to Employee Turnover ...

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9th international conference on Communication and Electronics systems, ICCES 2024

作者： Ponmalar, S. Affrin Fowmiya, N. Nandhini, C. Velammal College of Engineering and Technology Department of Computer Science and Engineering Tamilnadu Madurai India

ISBN: (纸本)9798350377972

Predictive analytics by combining ensemble learning and deep learning techniques. the first step normalizes the feature space with MinMaxScaler, which improves the performance of the algorithms. To tackle class imbalances, the Synthetic Minority Over-sampling Technique (SMOTE) is used, ensuring strong predictive modeling. An empirical study shows the effectiveness of various algorithms, including ensemble methods like CatBoost, AdaBoost, LightGBM, and Gradient Boosting Machine (GBM), whicheffectively capture complex interactions and nonlinear relationships in employee data. Furthermore, Long Short- Term Memory (LSTM) networks are employed to identify temporal dependencies in longitudinal records. the findings emphasize the approach's capability to detect subtle signals of potential turnover. By integrating these methodologies, this research provides HR professionals with valuable tools for proactive retention strategies. Ultimately, it advances HR analytics, assisting organizations in reducing attrition risks and promoting an engaged workforce. © 2024 ieee.

关键词： Predictive analytics

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