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9th International Conference on Intelligent Informatics and BioMedical sciences, ICIIBMS 2024

作者： Qiu, Chendi Zhou, Lanfeng Shanghai Institute Of Technology School of Computer Science & Information Engineering Shanghai China Shanghai Institute Of Technology Shanghai China

ISBN: (纸本)9798350363043

Capsule network(CapsNet) is an improvement of the classic convolutional neural network(CNN), which has achieved good results in the field of image classification. However, the high computational complexity of the routing process hinders them from building larger models. Fortunately, reducing the complexity of CapsNet routing through spatial attention mechanisms has achieved significantly good results. To this end, we propose a capsule network based on residual pose routing and attention mechanism. While reducing the routing calculation complexity, the accuracy can be improved. Experimental results on MNIST, CIFAR-10 and SmallNORB show that the proposed method can achieve better classification results compared with traditional methods. © 2024 IEEE.

关键词： Convolutional neural networks

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Evolutionary Optimization Methods for High-Dimensional Expensive Problems:A Survey

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IEEE/CAA Journal of Automatica Sinica 2024年第5期11卷 1092-1105页

作者： MengChu Zhou Meiji Cui Dian Xu Shuwei Zhu Ziyan Zhao Abdullah Abusorrah Department of Electrical and Computer Engineering New Jersey Institute of TechnologyNewarkNJ 07102 USA School of Information and Electronic Engineering Zhejiang Gongshang UniversityHangzhou 310018China School of Intelligent Manufacturing Nanjing University of Science and TechnologyNanjing 210094China Institute of Systems Engineering Macao University of Science and TechnologyMacao 999078China School of Artificial Intelligence and Computer Jiangnan UniversityWuxi 214122China School of Information Science and Engineering Northeastern UniversityShenyang 110819China Center of Research Excellence in Renewable Energy and Power Systems Department of Electrical and Computer EngineeringFaculty of EngineeringKing Abdulaziz UniversityJeddah 21589Saudi Arabia K.A.CARE Energy Research and Innovation Center King Abdulaziz UniversityJeddah 21589Saudi Arabia

Evolutionary computation is a rapidly evolving field and the related algorithms have been successfully used to solve various real-world optimization *** past decade has also witnessed their fast progress to solve a class of challenging optimization problems called high-dimensional expensive problems(HEPs).The evaluation of their objective fitness requires expensive resource due to their use of time-consuming physical experiments or computer ***,it is hard to traverse the huge search space within reasonable resource as problem dimension *** evolutionary algorithms(EAs)tend to fail to solve HEPs competently because they need to conduct many such expensive evaluations before achieving satisfactory *** reduce such evaluations,many novel surrogate-assisted algorithms emerge to cope with HEPs in recent *** there lacks a thorough review of the state of the art in this specific and important *** paper provides a comprehensive survey of these evolutionary algorithms for *** start with a brief introduction to the research status and the basic concepts of ***,we present surrogate-assisted evolutionary algorithms for HEPs from four main *** also give comparative results of some representative algorithms and application ***,we indicate open challenges and several promising directions to advance the progress in evolutionary optimization algorithms for HEPs.

关键词： computer optimization evolutionary

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Rule and Encryption based Secure Routing for Internet of Vehicle Networks 2

Rule and Encryption based Secure Routing for Internet of Veh...

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2nd IEEE International Conference on Networking and Communications, ICNWC 2024

作者： Anand, M. Muthurajkumar, S. Selvi, M. Thangaramya, K. Svn, Santhosh Kumar Kannan, A. Anna University Madras Institute of Technolog Department of Computer Technology Chennai India Vellore Institute of Technology School of Computer Science and Engineering Vellore India Vellore Institute of Technology School of Computer Science Engineering and Information Systems Vellore India

ISBN: (纸本)9798350365269

The Internet of Vehicles (IoV) has become one challenging communication technology in the current internet world. IoV enables real-time data exchange between vehicles, road infrastructures, and mobile communication devices and hence it helps in information exchange to vehicle drivers and the passengers. In IoV, Cybersecurity threats including Denial-of-Service (DoS) attacks are present and it compromises the security in communication among the vehicles and the passengers. Therefore, it is needed to develop a robust security mechanism that can protect the data communicated through routing in IoV. The inclusion of Encryption and Signature verification techniques in the routing algorithm will enhance the security. This paper proposes a Rule with Encryption-Oriented Secure Routing Protocol (REO-SRP) is proposed using clustering and RSA encryption with DSA Digital signature verification with rules for routing. Here, routing is performed after encryption of data and analysis of other vehicles using rules for reliable and secured data delivery. © 2024 IEEE.

关键词： Vehicles

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Advancing Plant Disease Prediction Accuracy with ViT Based Deep Learning Model

Advancing Plant Disease Prediction Accuracy with ViT Based D...

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2024 IEEE International Conference on Computing, Semiconductor, Mechatronics, Intelligent Systems and Communications, COSMIC 2024

作者： Sam, Felicita Kavitha, B.R. School of Computer Science Engineering and Information Systems Vellore Institute of Technology TamilNadu Vellore India

ISBN: (纸本)9798331517892

Agriculture is the key source for many people's livelihoods and an important contributor to a country's economy. There is a huge demand to streamline the process in the field of agriculture by integrating Computing into the traditional way of farming. Computing plays a key role in handling this sector with many newer revolutions that would automate the various processes involved in overall farming. Particularly, machine and deep learning based models have shown remarkable results in smart farming. Rice crop is considered in this work which is the major crop in India. It is necessary to meet the demands of the growing population in terms of sufficient production of this crop. One of the key issues in this crop is the plant diseases that impact the overall crop yield production considerably. Among the various diseases, the most commonly occurring disease is White stem Borer. Diagnosing the disease at an early stage could treat the problem at the earliest to ensure the appropriate amount of yield production. In this paper, a Vision transformer (ViT) based deep learning model is proposed to predict the white stem borer disease on the PlantDoc dataset and the results obtained are compared with the other promising CNN based pre trained models like VGG19, InceptionV3, Resnet50. The experimental output shows that Vision transformer based model outperforms the other proven models with an accuracy of 96%. © 2024 IEEE.

关键词： Plant diseases

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Method for background replacement of certification photos

Method for background replacement of certification photos

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2024 International Conference on Optics, Electronics, and Communication engineering, OECE 2024

作者： Chen, Xu Zhang, Jihong Du, Yufei Sha, Zihuan Qiu, Rongfei Xu, Zezhong School of Computer Science and Information Engineering Changzhou Institute of Technology Jiangsu Changzhou213032 China

ISBN: (纸本)9781510685437

In order to overcome defects resulted from replacing the photo background color, an improved method is proposed for background replacement. The α-values in the alpha matte are transformed to enhance the details in the transition area. The new photo is composited by comprehensively considering the foreground portrait, new background, old background and the alpha matte. The experimental results show that the foreground portrait appears clearer and more complete, and the transition area between the foreground and background is more harmonious and more natural. © 2024 SPIE.

关键词： Color Opacity computer science engineering Image processing Image processing algorithms and systems Image processing software Image segmentation information science

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Advancing Gender, Age and Ethnicity with YOLOv5 and Transfer Learning 6th

Advancing Gender, Age and Ethnicity with YOLOv5 and Transfer...

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6th International Conference on information Systems and Management science, ISMS 2023

作者： Bhattacharya, Varun Tripathy, Balakrushna School of Computer Science Engineering and Information Systems Vellore Institute of Technology Vellore632014 India

ISBN: (纸本)9783031664090

The detection of gender, age, and ethnicity using machine learning techniques holds significant promise for applications in marketing, healthcare, and law enforcement. Previous methods relied on conventional machine learning and manual feature engineering, which often struggled to capture the complex relationships between facial features and these demographic factors. To overcome these limitations, our novel approach leverages the powerful YOLOv5 framework, integrating transfer learning and deep neural networks. This cutting-edge method excels at accurately classifying gender, age, and ethnicity from facial images, thanks to its deep neural network architecture with advanced object detection capabilities. Our work represents a substantial advancement in gender, age, and ethnicity prediction, showcasing the potential of advanced machine learning techniques. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Adversarial machine learning

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The Threat of Quantum Computing to the Cryptographic Security of Blockchain 2

The Threat of Quantum Computing to the Cryptographic Securit...

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2nd International Conference on Emerging Trends in information technology and engineering, ic-ETITE 2024

作者： Modi, Pranit Asgola, Abhishek Mishra, Hiya Charanya, R. School of Computer Science Engineering and Information Systems Vellore Institute of Technology Vellore Vellore India

ISBN: (纸本)9798350328202

Blockchain technology, born as the backbone of cryptocurrencies like Bitcoin, has rapidly expanded into a versatile platform spanning various industries. This review paper delves into the critical aspects of security and anonymity within blockchain applications. It simplifies complex technical concepts while exploring the foundation of blockchain security, including cryptography, decentralization, consensus mechanisms, and the challenges posed by smart contracts. Additionally, it examines the pseudonymous nature of blockchain addresses, privacy-enhancing cryptocurrencies, and the delicate balance between transparency and anonymity. As we navigate these intricacies, we address challenges such as scalability, regulatory concerns, and potential threats from quantum computing. This paper aims to provide a comprehensive yet easily digestible understanding of the security and anonymity dimensions in blockchain applications. © 2024 IEEE.

关键词： Blockchain

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Smart Surveillance Object Detection System 3

Smart Surveillance Object Detection System

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3rd International Conference on Artificial Intelligence For Internet of Things, AIIoT 2024

作者： Chaudhary, Gaurav Pathak, Shreya Choudhary, Vikas Chauhan, Love Tripathi, Abhishek N School of Electronics Engineering Vellore Institute of Technology Vellore India School of Computer Science Engineering and Information Systems Vellore Institute of Technology Vellore India

ISBN: (纸本)9798350372120

This paper presents an integrated Internet of Things based approach to smart surveillance and urban parking management systems, emphasizing robust object detection and precise parking occupancy monitoring. Our solution adopts cost-effective hardware like the ESP32 CAM module, leveraging its built-in camera and powerful processor for real-time image processing. For surveillance applications, we implement a custom object detection model built with OpenCV, a renowned Python library. This model, finely-tuned for efficient person detection, runs directly on the ESP32 CAM, eliminating the need for external processing units. Additionally, the ESP32 CAM's Wi-Fi connectivity enables seamless integration with existing networks, simplifying deployment. This integrated approach, combining the cost-effectiveness of ESP32 CAM modules with the image processing capabilities of OpenCV, offers a comprehensive solution for smart surveillance and urban parking management. By utilizing readily available hardware and open-source software, the system promotes widespread adoption and affordability, making it a valuable tool for creating smarter and more sustainable cities. © 2024 IEEE.

关键词： computer vision

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Multiuser Computation Offloading for Long-Term Sequential Tasks in Mobile Edge Computing Environments

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Tsinghua science and technology 2023年第1期28卷 93-104页

作者： Huanhuan Xu Jingya Zhou Wenqi Wei Baolei Cheng School of Computer Science and Technology Soochow UniversitySuzhou 215006China State Key Laboratory of Mathematical Engineering and Advanced Computing Wuxi 214125China Provincial Key Laboratory for Computer Information Processing Technology Soochow UniversitySuzhou 215006China School of Computer Science Georgia Institute of TechnologyAtlantaGA 30332USA

Mobile edge computing has shown its potential in serving emerging latency-sensitive mobile applications in ultra-dense 5G networks via offloading computation workloads from the remote cloud data center to the nearby network ***,current computation offloading studies in the heterogeneous edge environment face multifaceted challenges:Dependencies among computational tasks,resource competition among multiple users,and diverse long-term *** applications typically consist of several functionalities,and one huge category of the applications can be viewed as a series of sequential *** this study,we first proposed a novel multiuser computation offloading framework for long-term sequential ***,we presented a comprehensive analysis of the task offloading process in the framework and formally defined the multiuser sequential task offloading ***,we decoupled the long-term offloading problem into multiple single time slot offloading problems and proposed a novel adaptive method to solve *** further showed the substantial performance advantage of our proposed method on the basis of extensive experiments.

关键词： mobile edge computing sequential tasks computation offloading dependency

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Change Vector Change Indices Method for Unsupervised Remote Sensing Change Detection

Change Vector Change Indices Method for Unsupervised Remote ...

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2024 International Conference on Signal Processing, Computation, Electronics, Power and Telecommunication, IConSCEPT 2024

作者： Sujith Kumar, A. Sundaram, Venkatesan Meenakshi Prabhavathy, P. National Institute of Technology Department of Computer Science and Engineering Puducherry India School of Computer Science Engineeering and Information Systems Vellore Institute of Technology Vellore India

ISBN: (纸本)9798331540685

Unsupervised Remote sensing change detection is very important because it addresses the problem of scarcity in the data availability in training. Some of the researchers are successful in finding the change regions but are not able to classify what changes happened in those regions. Nearly every study faces challenges in generalizing the fluctuations occurring during both the growing and non-growing seasons. The current study utilizes a novel architecture consisting of two parts. The first part involves proposing change regions through the change vector calculation method and applying Otsu's Thresholding on the calculated change vectors, while the second part entails classifying these proposed change regions into vegetation change, building change, and non-change regions. non-change region classification process aims to eliminate false changes identified by the change vector analysis and Otsu's Thresholding. In the second stage, NDVI, NDWI, and NDMI indices are compared and the resulting change mask obtained is subjected for element-wise multiplication operation with the change mask obtained in the first stage. The study addressed the challenge of generalizing short-term changes, such as those occurring during the growing and non-growing seasons, by computing the median of pixels over a time range encompassing both types of changes. Additionally, the method was fine-tuned using NIT Puducherry data from two time periods. Subsequently, the entire Karaikal district was considered to examine the changes comprehensively. The present study outperformed different state of the art methods like CVI_OTSU, PCI_Kmeans, Continuous Change Detection and Classification (CCDC). The present study got better results with an accuracy of 86.07 and kappa coefficient of 0.7898. © 2024 IEEE.

关键词： Change detection

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