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检索条件"任意字段=2022 International Conference on Algorithms, Network and Computer Technology, ICANCT 2022"

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RBAS: Randomized Bi-Phase Authentication Scheme for Wireless Internet of Things Sensor networks

RBAS: Randomized Bi-Phase Authentication Scheme for Wireless...

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2022 international conference on Smart Applications, Communications and networking, SmartNets 2022

作者： Phalaagae, Pendukeni N. Zungeru, Adamu Murtala Sigweni, Boyce Rajalakshmi, Selvaraj Botswana International University of Science and Technology Department of Electrical Computer and Telecommunications Engineering Palapye Botswana Botswana International University of Science and Technology Department of Computer Science and Information Syestems Palapye Botswana

ISBN: (纸本)9781665487580

Wireless internet of things sensor networks are made up of a network of sensors which continually transmit sensed data from their environment to the sink through wireless communication. Therefore, maintaining the consistency, trustworthiness of information sent to the sink is vital to assure privacy and integrity of information. However, preserving the privacy of routed messages remains a challenge despite efforts made by prior researchers. Consequently, the mechanisms proposed do not adequately address message confidentiality after authenticating nodes in the network. A lightweight, energy-authentication scheme that provides both outside and inside network security, termed Randomized Bi-Phase Authentication Scheme (RBAS), is proposed, which helps to detect various types of tampering on the data. The proposed scheme has demonstrated to minimize total energy consumption by 8% over the existing BAS authentication scheme. © 2022 IEEE.

关键词： Authentication

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A Review of Multi-Label Feature Selection 3

A Review of Multi-Label Feature Selection

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3rd international conference on computer, Big Data and Artificial Intelligence, ICCBDAI 2022

作者： Wang, Xiujuan Zhou, Yuchen Beijing University of Technology Faculty of Information and Technology Beijing100020 China Beijing University of Technology Beijing-Dublin International Technology Beijing100020 China

Feature selection has become a vital issue in data mining and machine learning. But some challenges have been outstanding when trying to improve the performance of feature selection, such as small sample, uncertain classes, complex features, complementation and redundancy between each feature. In this paper, firstly the background of feature selection is introduced. Then we have presented a new perspective to analyze multi-label feature selection and provided typical papers on different classifications. To further analyze these algorithms, evaluation criterion on results of multi-label feature selection is summarized. Finally, some reflects on research directions, future works and conclusions are organized. © Published under licence by IOP Publishing Ltd.

关键词： Feature Selection

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Single image super-resolution via deep learning 3

Single image super-resolution via deep learning

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3rd international conference on computer Vision, Image and Deep Learning and international conference on computer Engineering and Applications, CVIDL and ICCEA 2022

作者： Cao, Zhenyue Liu, Xuan Wang, Zhenkun Shenzhen College of International Education Shenzhen China Tongii University Shanghai China South China Agricultural University Guangzhou China

ISBN: (纸本)9781665459112

Single image Super-resolution (SISR) is a computer vision (CV) problem that aims to acquire a high-resolution (HR) image from a distorted low-resolution (LR) image, making it a valuable technology that could be utilized in various fields such as photography, medical imaging, satellite imaging, etc. As a result of the advancement of computing hardware and richer computational power, deep learning-based image super-resolution models have emerged at an unprecedented rate. This paper reviews SISR and its recent development. Three widely used deep architectures: convolutional neural network (CNN), generative adversarial network (GAN), and transformer are explained. Next, six different deep learning-based models that summarize research on SISR are analyzed. Finally, this review concludes with applications of SR, current challenges SISR models encountered, and potential future research directions. © 2022 IEEE.

关键词： Generative adversarial networks

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Thai Food Recognition Using Convolutional Neural network with Dropout Technique 7

Thai Food Recognition Using Convolutional Neural Network wit...

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7th international conference on Digital Arts, Media and technology, DAMT 2022 and 5th ECTI Northern Section conference on Electrical, Electronics, computer and Telecommunications Engineering, NCON 2022

作者： Natephakdee, Niti Temdee, Punnarumol Srimaharaj, Wanus Building Research Center School of Information Technology Mae Fah Luang University Computer and Communication Engineering for Capacity Chiang Rai Thailand Payap University The International College Department of Information Technology Chiang Mai Thailand

ISBN: (纸本)9781665495103

Visually recognizing Thai food is indeed a challenging task and tradition methods have achieved historically low classification. While deep learning operation allows users to identify Thai cuisine and visually distinguish Thai food, it often includes complex meanings. The deep learning approach has shown very satisfied results in such challenges. Therefore, this study focuses on presenting methods and techniques for noise reduction of Thai food images used in image recognition. A total of sixty thousand sample images were used in the experiment. Results revealed that the method offered highest reliable accuracy of 94.16%. © 2022 IEEE.

关键词： Deep learning

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Discrete-time Recurrent Neural network Algorithm with Different Discretization Formulas for Finding Solution of Discrete-Time Complex Division 11

Discrete-time Recurrent Neural Network Algorithm with Differ...

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11th IEEE Data Driven Control and Learning Systems conference, DDCLS 2022

作者： Shi, Yang Lu, Jiwen Zhao, Wenhan Sheng, Wangrong Li, Jian Gerontitis, Dimitrios K. School of Information Engineering Yangzhou University Yangzhou225127 China Jiangsu Province Engineering Research Center of Knowledge Management and Intelligent Service Yangzhou University Yangzhou225127 China School of Computer and Information Technology Xinyang Normal University Xinyang464000 China International Hellenic University Department of Information and Electronic Engineering Thessaloniki57400 Greece

ISBN: (数字)9781665496759

ISBN: (纸本)9781665496759

In this paper, in order to solve discrete-time complex division, we propose several discrete-time recurrent neural network (DT-RNN) algorithms. First of all, the continuous-time complex division is transformed into matrix equation equivalently, which can be solved by the continuous-time recurrent neural network (CT-RNN) algorithm. Secondly, several discretization formulas developed by Taylor formula are used to establish the corresponding DT-RNN algorithms. Finally, numerical experiments are carried out, which present the feasibility and effectiveness of these DT-RNN algorithms. © 2022 IEEE.

关键词： Complex networks

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Risk Assessment of Lane Change Status for Intelligent Vehicle Based on Fuzzy Bayesian 6

Risk Assessment of Lane Change Status for Intelligent Vehicl...

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6th international conference on computer network, Electronic and Automation, ICCNEA 2023

作者： Qi, Lei Du, Feng Du, Yuyang Cheng, Jianfeng Du, Qiong Ji, Penghao Tianjin University of Technology and Education School of Automotive and Transportation Tianjin China Dalian University of Technology Leicester International Institute Panjin China

ISBN: (纸本)9798350305388

A multi-factor fusion risk assessment approach for lane shifting state is designed with the goal of increasing the safety of lane changing in the human-machine co-driving environment of intelligent vehicles. To begin, the urban road traffic risk factors are described at three levels: "human, vehicle, and road"to create the driving risk factor set;then, the key indicators are screened using principal component analysis;and finally, the vehicle lane change risk level is identified by combining fuzzy theory and Bayesian network. The experimental and computational results show that the fuzzy Bayesian network model accurately reflects the impact of several factors on driving safety, with weather and acceleration having the most influence. Simultaneously, when compared to the traditional Bayesian network, this method can effectively compensate for the Bayesian network's inference precision shortcomings, accurately determine the degree of danger of lane-changing behavior, and determine the current driver's risk level as a potential risk (level IV), which provides a theoretical basis for when to make a safe switch of the driving right in the intelligent vehicle human-computer co-pilot system and how to select the lane-changing strategy. © 2023 IEEE.

关键词： Risk assessment

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An Improved BP Neural network-based Quality Evaluation Model for Chinese international Education Teaching Courses 2022

An Improved BP Neural Network-based Quality Evaluation Model...

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6th international conference on Compute and Data Analysis, ICCDA 2022

作者： Huang, Binxian Wang, Ke School of Literature Journalism Communication Xihua University China

ISBN: (纸本)9781450395472

For learners of Chinese as a second language, it is difficult to learn Chinese in the target language environment. With the large-scale applications of intelligent technology in Chinese international education, Chinese teaching is moving towards digitalization, networking and informatization, and computer technology is promoting the development of Chinese international education in a more convenient way. In order to effectively improve the teaching quality of Chinese international education, a scientific and reasonable evaluation system of course teaching quality needs to be formulated. This paper addresses the shortcomings of the traditional course teaching quality evaluation methods, introduces BP neural network to establish the teaching evaluation base model, and sets the corresponding course evaluation indicatores as the input quantity. Considering the problems of local optimum and low convergence efficiency of BP neural network, an improved BP neural network is proposed to optimize the initial weights and thresholds of BP neural network using the beetle antennae search algorithm, so as to obtain the improved teaching quality evaluation model of Chinese international education courses. Then, the performance test of the model is conducted in this paper. The test results show that the proposed teaching quality evaluation model can accurately evaluate the teaching quality of the curriculum and help improve the teaching courses of Chinese international education, which is an innovative attempt to combine computer technology with Chinese international education. Finally, this paper puts forward corresponding suggestions for the combination of Chinese international education and computer technology, in order to promote the further development of Chinese international education. © 2022 ACM.

关键词： Quality control

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The Application of Graph Theory for The networking of Rural Agriculture Products Marketing

The Application of Graph Theory for The Networking of Rural ...

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2022 international conference on Communication, Computing and Internet of Things, IC3IoT 2022

作者： Hossen, Md. Shahed Nesa, Ezzatun Sristy, Arpita Mony Ahmed, Fizar Daffodil International University Dept. of Computer Science and Engineering Dhaka Bangladesh

ISBN: (纸本)9781665479950

Graph theory has the potential to become a major subject of study shortly. However, graph theory research is still in its infancy. In order to build a network mesh, graph theory is quite useful. The use of graph theory to agriculture has the potential to be a game-changer. In addition to marketing networks, graph theory may be used to conduct new research in areas such as fraud detection and recommendation systems. Graph theory has been used by large corporations such as Facebook to create network networks among its clients. Facebook envisioned a network with vertices representing a group of friends. One advantage is that every one of them will be connected via their Facebook connections. And graph theory is highly useful in constructing such a network. We used graph theory to design a marketing network for a rural agricultural commodity in this article. To create this network, we used a variety of graph theory methodologies and algorithms, including the Breadth-First Search (BFS) algorithm. We'll walk you through this network visualization using Python's networkX module. © 2022 IEEE.

关键词： Graph theory

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international conference on Computational Intelligence in Machine Learning, ICCIML 2021

International Conference on Computational Intelligence in Ma...

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international conference on Computational Intelligence in Machine Learning, ICCIML 2021

ISBN: (纸本)9789811684838

The proceedings contain 51 papers. The special focus in this conference is on Computational Intelligence in Machine Learning. The topics include: Recognizing Art Style Automatically in Painting Using Convolutional Neural network;violence Recognition Using Convolutional Neural networks;the Future of Car Automation Field with Smart Driverless Technologies;Fault Classification of Cooling Fans Using a CNN-Based Approach;Hybrid Model Seasonal ARIMA-LSTM for Prediction Water Level in Black River on the Border Vietnam-China;Fuzzy Logic in Battery Energy Storage System (BESS);applications of Machine Learning in Anomaly Detection;design and Development of an Algorithm for Automatically Capturing and Recognizing the Number Plates of Vehicles—A Surveillance System to Support Indian Traffic Police;data Security Using Cryptography and Steganography Technique on the Cloud;data Security in Cloud Computing Using a Hybrid Algorithm Approach;automated Detection of Cataract Using a Deep Learning Technique;Machine Vison-Based System for Vehicle Classification and Counting Using YOLO;Deep Learning Based Model for COVID-19 Pneumonia Prediction with Pulmonary CT Images;fuzzy Logic Control for Quadrotor Micro-aerial Vehicle Altitude and Attitude Stabilization;placement Analysis—A New Approach to Ease the Recruitment Process;machine Learning Concept in Smart Water Purifier and Dispenser for Averting Spread of Infections;smart Irrigation for Enhanced Agriculture Production Using IoT;seafloor Habitat Mapping Using Machine Learning and Underwater Acoustic Sonar;a Study of Glaucoma Diagnosis Using Brain–computer Interface technology;A Survey on DDoS Attacks from Compromised Devices to Enhance IoT Security;anomalous Behavior Detection in Examination;depressive Bangla Text Detection from Social Media Post Using Different Data Mining Techniques;program Synthesis—A Survey.

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Neural network quantization algorithms based on weights and activation values

Neural network quantization algorithms based on weights and ...

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2022 international conference on algorithms, Microchips and network Applications

作者： Li, Yubo Wang, Runbo Wu, Huaping International College Zhengzhou University Zhengzhou450000 China College of Electronic Information and Automation Civil Aviation University of China Tianjin300300 China Business Management University of the Pacific Stockton95211 United States

ISBN: (纸本)9781510653290

In recent years, neural networks have demonstrated attractive performance in a variety of computer vision tasks. This has led to the deployment of CNNs into real-world applications. However, most existing CNNs require a large amount of storage space and computational resources, which hinders their deployment on mobile devices. In order to solve this problem, the existing research shows that quantization and pruning can greatly reduce the memory occupied by the neural network in the device without reducing the accuracy of image recognition, which plays a great role in solving the deployment problem of CNNs. Therefore, this paper classifies and analyzes the quantitative algorithm model of neural network according to the parameters that need to be quantified, summarizes the common defects of the current quantitative algorithm in terms of accuracy, and looks forward to its future development trend. © COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.

关键词： Chemical activation

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