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检索条件"任意字段=International Conference on Computer Engineering and Technology"

共 438506 条记录，以下是551-560 订阅

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Investigating the Effects of AI-Driven Systems on Data Science Automation 15

Investigating the Effects of AI-Driven Systems on Data Scien...

引用

15th international conference on Computing Communication and Networking Technologies, ICCCNT 2024

作者： Senthilkumar, K.K. Mehta, Pradnya S. Pandey, Megha Rao, Panduranga M.V. Singh, Baldev Khurana, Saniya Department of Electronics and Communication Engineering Prince Shri Venkateshwara Padmavathy Engineering College Chennai127 India Department of Computer Engineering Vishwakarma Institute of Information Technology Pune India Maharishi School of Engineering and Technology Maharishi University of Information Technology Uttar Pradesh India Karnataka Bangalore India Department of Computer Science & Engineering Vivekananda Global University Jaipur India Centre of Interdisciplinary Research in Business and Technology Chitkara University Institute of Engineering and technology Chitkara University Punjab India

ISBN: (纸本)9798350370249

This article investigates the effect of AI-driven structures on the automation of information science. AI-pushed structures and automation of records technology have ended up an increasing number of essential because of the growing complexity of information and the numerous and ever-increasing data resources in today's digital international. This text explores the approaches in which AI-driven structures have converted how records technology is being computerized and the way it has impacted the method. Moreover, the article looks at the benefits and shortcomings of AI-driven structures in terms of automation of data science as well as the various regions which are still open for research that allows you to, in addition, improve the automation of information technology. Finally, the article proposes future study guidelines in this field, allowing the continued development of AI-driven records science automation. ©2024 IEEE.

关键词： automated information proposes shortcomings transformed

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A Tourism Product Design System Utilizing computer Sensors and VR technology 2

A Tourism Product Design System Utilizing Computer Sensors a...

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2nd IEEE international conference on Electrical, Automation and computer engineering, ICEACE 2024

作者： Bin, Li Wuhan Railway Vocational College of Technology Wuhan430205 China

ISBN: (纸本)9798350368208

The integration of computer sensors and virtual reality (VR) technology plays a crucial role in advancing the tourism industry by creating immersive and interactive experiences for consumers. This research study investigates the development of a tourism product design system that leverages both computer sensor technologies and VR to enhance user engagement and product innovation. Using a moderated mediation framework, the study explores how tourism products can be designed to optimize user experiences through real-time data collection from sensors, combined with immersive VR environments. The findings highlight the increasing role of sensor-based data in enhancing the accuracy and personalization of tourism product design. Additionally, the study reveals the growing potential of VR systems to transform how tourism products are conceptualized and marketed. Future research could further explore the integration of augmented reality systems and advanced sensors to improve the interactivity and adaptability of tourism products within virtual spaces. © 2024 IEEE.

关键词： Augmented Reality Systems computer Sensors Technological Advancements Tourism Products Virtual Reality Technologies

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Brain Tumor Detection: A Comprehensive Review 5

Brain Tumor Detection: A Comprehensive Review

引用

5th international conference on Electrical, Communication and computer engineering, ICECCE 2024

作者： Bhagat, Poonam Pandian, R. Sathyabama Institute of Science and Technology Computer Science and Engineering Chennai India Sathyabama Institute of Science and Technology Electronics and Communication Engineering Chennai India

ISBN: (纸本)9798331529437

Brain tumor classification and segmentation are crucial medical imaging procedures that aid in diagnosis and treatment planning. This study provides a detailed analysis of the methodologies and techniques used in this subject, which includes conventional machine learning (ML), convolutional neural networks (CNNs), capsule networks (CapsNets), and vision transformers (ViTs). This survey identifies key challenges and opportunities in brain tumor analysis and delineates future research directions. Extant literature predominantly focuses on individual tasks such as tumor detection, segmentation, or grade estimation, indicating the necessity for integrated frameworks capable of simultaneous multi-tasking, particularly with multi-grade classification. While CNNs have been extensively utilized, alternative architectures such as CapsNets and ViTs offer promising avenues for enhancing diagnostic accuracy and efficiency. © 2024 IEEE.

关键词： Convolutional neural networks

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The Multi-Way Path Over the Blockchain: The Development of the Security Algorithm RB-24-1 6

The Multi-Way Path Over the Blockchain: The Development of t...

引用

6th international conference on Mobile Computing and Sustainable Informatics, ICMCSI 2025

作者： Rajaprakash, S. Bagath Basha, C. Rathish Babu, T.K.S. Karthik, S. Subapriya, V. Kavitha, S. Department of Computer Science & Engineering Vel Tech Rangarajan Dr.Sagunthala R&D Institute of Science and Technology Tamil Nadu Chennai India Department of Computer Science & Engineering Kommuri Pratap Reddy Institute of Technology Telagana Hyderabad India Department of Computer Science & Engineering SRM Institute of Science and Technology Ramapuram Tamil Nadu Chennai India Department of Computer Science & Engineering Aarupadai Veedu Institute of Technology Vinayaka Missions Research Foundation Tamil Nadu Chennai India Department of Computer Science & Engineering Sathyabama Institute of Science and Technology Tamil Nadu Chennai India

ISBN: (数字)9798331522667

ISBN: (纸本)9798331522667

In the current world, a lot of new technologies are becoming famous. The Block Chain is one of these technologies. A very high amount of safety is offered by the technology in question;it is extremely robust. Users are not privy to a great deal of information regarding Block Chain;however, Protecting the data that is sent in multiple ways is what its security features are for. The "SalSa and RBJ25 algorithms" were still being used by this person. We are going to talk about the new "security mechanism" we have named RB-24-1. This method is comprised of these four different techniques. The procedure begins with the "Latin Alphabet code" being assigned to T. This is the first step in the process. To proceed to the next step, use Equation (1) to perform four times the multiplication of the number by itself. "Exchanging the values of the cells" is what the third step does., and it is carried out with the help of encrypted data. Putting the "SalSa" algorithm into action within the matrix constitutes the fourth step throughout the process. Finally, the plain text is converted into the encrypted text format. This has been a long time coming. There is a higher level of security offered by the method that has been suggested in compare and contrast with the method that is being used at the moment. © 2025 IEEE.

关键词： Encryption algorithms

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DFaker++: high-fidelity face swapping technology based on attention mechanism 3

DFaker++: high-fidelity face swapping technology based on at...

引用

3rd international conference on Electronic Information engineering, Big Data, and computer technology, EIBDCT 2024

作者： Shao, Wenhua Wang, Xiaodong Zeng, Zhiqiang Wu, Longpei School of Computer and Information Engineering Xiamen University of Technology Xiamen China

ISBN: (纸本)9781510680449

In the era of artificial intelligence, face swapping technology has demonstrated its unique application value and broad prospects. Nevertheless, current research methods often struggle to achieve both rapidity and high quality while pursuing high-fidelity facial synthesis. In view of this, our study innovates on traditional models and integrates attention mechanisms, proposing a novel high-fidelity face swapping method1/4DFaker++. In terms of implementation, we first optimized and improved existing algorithms;secondly, by introducing an attention mechanism, the model can automatically focus on key facial areas in both source and target images, thereby more effectively preserving and blending facial features. Additionally, we employ the Huber loss function to guide model training, which shows better performance in cases with high noise or imperfect inputs. We propose a novel evaluation method for face swapping that merges objective metrics with subjective assessments, focusing on the quality of facial generation. Our experiments demonstrate that this approach outperforms existing models in both quality and efficiency, marking a significant step forward in facial synthesis technology. © COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.

关键词： Image enhancement

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Multivariate time series anomaly detection based on sparse autoencoder and dynamic graph attention network 5

Multivariate time series anomaly detection based on sparse a...

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5th international conference on computer Vision and Data Mining, ICCVDM 2024

作者： Li, Hui Zhang, Suli School of Information and Control Engineering Jilin Institute of Chemical Technology Jilin132022 China School of Computer Technology and Engineering Changchun Institute of Technology Changchun130012 China

ISBN: (纸本)9781510682863

With the further advancement of industrial technology, the data generated by sensors is gradually becoming more complex. Deep learning approaches have made notable strides in the domain of anomaly detection, especially when it comes to high-dimensional datasets. However, most existing methods neglect the complex relationships between feature dimensions and the dependencies between multiple time steps, resulting in insufficient extraction of key feature information. In response to this problem, our paper introduces a model for detecting anomalies in multivariate time series, utilizing Sparse Autoencoder and Dynamic Graph Attention Network (SAE-GATv2). The outcomes of experiments conducted on two actual sensor datasets reveal that our suggested approach is capable of identifying anomalies with greater precision and showcases superior overall performance in comparison to the baseline methods. © 2024 SPIE.

关键词： Sensors Data modeling Education and training Feature extraction Neurons Performance modeling Artificial neural networks Deep learning Matrices engineering

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Smart UV Analyzer for Pesticide Residues Detection Using TLC Based On Image Processing 9

Smart UV Analyzer for Pesticide Residues Detection Using TLC...

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Joint 9th international conference on Digital Arts, Media and technology with 7th ECTI Northern Section conference on Electrical, Electronics, computer and Telecommunications engineering, ECTI DAMT and NCON 2024

作者： Ounyoung, Natthpon Jaita, Subin Mettripun, Narong Rajamangala University of Technology Lanna Chiang Rai Faculty of Engineering Department of Electrical Engineering Chiang Rai57120 Thailand Rajamangala University of Technology Lanna Chiang Rai Faculty of Science and Agriculture Technology Chiang Rai57120 Thailand

ISBN: (纸本)9798350318241

In this paper, we propose the smart UV analyzer for pesticide residues detection using Thin-layer Chromatography (TLC) based on image processing. The proposed method aims to reduce the time-consuming of the conventional method that uses an ordinary UV analyzer. Meanwhile, the proposed method requires no specialist staff and can avoid harmful UV radiation from an ordinary UV Analyzer. The smart UV analyzer consists of 3 components: an inserting component, an I/O component, and a processor component, including an image processing program used to calculate the rate of flow (Rf) and identify the type of pesticide residue. In the experimental setting, 30 samples of vegetables were investigated. The experimental results show that the proposed method can reduce time consumption by 3.98 times per sample compared with the conventional method on average. © 2024 IEEE.

关键词： Thin layer chromatography

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Judicial System in Bangladesh Using Distributed Blockchain technology 3

Judicial System in Bangladesh Using Distributed Blockchain T...

引用

3rd international conference on Advancement in Electrical and Electronic engineering, ICAEEE 2024

作者： Rakibul Hasan, M.M. Kashem, Mohammod Abul Fatin, Md. Al-Abrar Roni, Md. Mainul Islam Bangladesh University of Professionals Department of Information and Communication Technology Dhaka Bangladesh International University of Business Agriculture and Technology Department of Computer Science and Engineering Dhaka Bangladesh Dhaka University of Engineering and Technology Department of Computer Science and Engineering Gazipur Bangladesh

ISBN: (纸本)9798350388282

The current judicial system process, which is conducted manually in Bangladesh, is characterized by a high degree of uncertainty and risk, as well as a wide range of possibilities for fraudulent documents and the preservation of the ownership details of cases. Therefore, the current system does not appear to be feasible, effective. We have created our proposed blockchain-based judicial management system with the SHA-256 data encryption technique. This system will ensure the safety of the case transactions and will be able to store, authenticate, and maintain entire pertinent information of the case document. The mentioned architecture will be able to revoke and to detect attempts to change the case by using a variety of technologies, including IPFS, Proof of Stack (PoS), and public-key cryptography. These techniques will lead to subsequent more efficient solutions than the existing systems and improve how the general public views Bangladesh's judicial system. © 2024 IEEE.

关键词： Blockchain

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Human Detection and Tracking using Machine Learning Algorithm

Human Detection and Tracking using Machine Learning Algorith...

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2024 international conference on Advances in Computing Research on Science engineering and technology, ACROSET 2024

作者： Nallasivan, G. Thatikonda, Ramya Geetha, M. Bhuvanesh, A. Ramraj, S. Sreethu, S. Vel Tech Rangarajan Dr. Sagunthala R&d Institute of Science and Technology Department of Computer Science and Engineering Chennai India University of the Cumberlands Department of Information Technology Williamsburg United States Sri Eshwar College of Engineering Department of Electrical and Electronics Engineering Coimbatore India Psn College of Engineering and Technology Department of Electrical and Electronics Engineering Tirunelveli India

ISBN: (纸本)9798350388800

The use of OpenCV and its capabilities for person tracking and detection is suggested by this project. The technique works well for following people in a variety of situations, such as busy places, people who are obscured, and people who are moving. The robustness and precision of the estimated model are illustrated through the use of visuals to visualize tracking data. The suggested approach surpasses existing sophisticated algorithms in terms of Intersection over Union (IoU) and mean Average Precision (mAP), achieving excellent accuracy. Potential applications for the proposed method include robots, human-computer interaction, and surveillance. The limits of the suggested approach are also covered, along with suggestions for further research and development. © 2024 IEEE.

关键词： Adversarial machine learning

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Two dimensional DOA estimation of coherent signals based on covariance matrix element transformation 24

Two dimensional DOA estimation of coherent signals based on ...

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8th international conference on Electronic Information technology and computer engineering, EITCE 2024

作者： Qu, Zhiyu Wu, Xu Geng, Zhenya College of Information Science and Engineering Hohai University Jiangsu Nanjing China College of Computer Science and Software Engineering Hohai University Jiangsu Nanjing China The 49th Research Institute of China Electronics Technology Group Corporation Heilongjiang Harbin China

ISBN: (纸本)9798400710094

Traditional Direction of Arrival (DOA) estimation algorithms for coherent signals in uniform circular array (UCA), such as mode space transformation, allow for the adaptation of advanced algorithms initially developed for uniform linear arrays to be applied effectively in UCA. However, after mode space transformation, the array will encounter aperture loss and will also be unable to perform two-dimensional DOA estimation effectively. In this paper, we propose a new method that that integrates covariance matrix element transformation with the Multiple Signal Classification (MUSIC) to estimate the DOA of coherent signals in various symmetric antenna arrays, including UCA. The algorithm leverages the phase difference symmetry of the antenna array to decorrelate the incoming signals, effectively restoring the full rank of the covariance matrix. Subsequently, it employs two-dimensional MUSIC for DOA estimation. Simulation results demonstrate the effectiveness of the proposed algorithm. © 2024 Copyright held by the owner/author(s).

关键词： Covariance matrix

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