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检索条件"任意字段=7th International Conference on Computing in Engineering and Technology, ICCET 2022"

共 11084 条记录，以下是481-490 订阅

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Comparative analysis of deepfake detection methods using machine learning and deep learning 7

Comparative analysis of deepfake detection methods using mac...

引用

7th international conference on Circuit Power and computing Technologies, ICCPCT 2024

作者： Agrawal, Poorva Pathak, Soham Potey, Shruti Dhengre, Vaishnavi Rakesh, Nitin Parvathi, R. Symbiosis Institute of Technology Nagpur Campus Pune India Dept. of Smart Computing Vellore India

ISBN: (纸本)9798350372816

the paper examines the growing issue of deepfake technology, which uses cutting-edge machine learning to spoof face features in videos. this technology has the potential to be abused in a number of situations, including blackmail, political manipulation, and the staging of terrorist acts. the study's main goal is to present a thorough summary of current studies that use cutting-edge deep learning techniques to identify fake information. the Deepfakes Detection Challenge (DFDC) dataset is introduced, neural network applications are covered, and the effectiveness of current deepfake detection models is assessed. Because deepfake applications potentially pose a hazard, the research emphasizes the need for tools that can automatically detect and evaluate the integrity of digital visual data. Additionally, it discusses numerous algorithms and approaches that have been put out in the literature for producing and identifying deepfakes, with a focus on deep learning-based methods. © 2024 IEEE.

关键词： Contrastive Learning

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Measurement of Sheet Resistance of Heated Coated Glass using Cylindrical Cavity Resonator 7

Measurement of Sheet Resistance of Heated Coated Glass using...

引用

7th IEEE international conference on Electronic Information and Communication technology, ICEICT 2024

作者： Liu, Wei Ye, Ming Yu, Gang Xi'an University of Architecture and Technology College of Information and Control Engineering Xi'an China State Key Laboratory of Green Building Materials Beijing China

ISBN: (纸本)9798350384437

Coated glass, as a common material for green building facades, may experience temperature change due to sunlight and its physical properties may thus be affected. Considering relation between the physical properties and sheet resistance of coated glass, this paper proposes a measurement method for sheet resistance of coated glass at temperatures higher than room temperature by using a cylindrical cavity resonator working with TE011 mode at around 28 GHz. A heating platform is used to heat the sample (from room temperature to 60°C). To minimize temperature variation of the cavity itself, an air gap, ranging from 0 ~ 2 mm, is introduced between the cavity and the sample. Preliminary results indicates that the sheet resistance of coated glass decreases with temperature which agree with existed publications. thus, the obtained results verified the feasibility and reliability of this measurement method. © 2024 IEEE.

关键词： Cavity resonators

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Prediction of Stroke Severity in Brain through Machine Learning 7

Prediction of Stroke Severity in Brain Through Machine Learn...

引用

7th international conference on Intelligent computing and Control Systems, ICICCS 2023

作者： Anuprabha, M.V. Madhumitha, K. Sowmyadevi, K. Jaspar Vinitha Sundari, T. Paramasivam, K. Kumaraguru College of Technology Dept. of Electronics and Communication Engineering Coimbatore India Kumaraguru College of Technology Dept.of Electrical and Electronics Engineering Coimbatore India

ISBN: (纸本)9798350397253

As per the statistics of world health organization, the death rate in adolescents and young adults is found to be 1.3 million in 2020. Increase in health issues among young adults and adolescents is observed at higher rates in the last decade. Brain stroke is one of the diseases which is silently making its progress from occurring across senior citizens to young adolescents. the point of the work is to decrease the possibility of brain stroke or better forestall them by taking input from the client and foreseeing the result considering the information entered. the entire process is done by utilizing AI methods and the functioning framework has acquired a precision of roughly 94.2%. Five unique classifiers namely Decision tree, KNN, Naive Bayes, Logistic regression and SVM are used in building vulnerability predictors and utilized in a few comparative explorations work. Additionally, these models are assessed by estimating the disarray grids by using Dataset from Kaggle. © 2023 IEEE.

关键词： Logistic regression

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Systematic Review of Emerging Deep Learning approaches for Crop Diseases detection 7

Systematic Review of Emerging Deep Learning approaches for C...

引用

7th international conference on Circuit Power and computing Technologies, ICCPCT 2024

作者： Vasuki Rohinidevi, V. Deeban Chakravarthy, V. Deepak, S. Prem Kumar SRM Institute of Science and Technology School of Computing Department of Computing Technologies Chennai India B V Raju Institute of Technology Department of Computer Science and Engineering Narsapur India

ISBN: (纸本)9798350372816

Deep learning, a branch of artificial intelligence, has drawn interest from the academic and corporate realms, especially in areas like speech and image analysis, video processing, and natural language processing. Its use in agricultural plant protection has expanded to include the diagnosis and evaluation of pests and plant diseases. In this situation, there are several benefits to using deep learning. It removes the biases related to manually chosen pathogen properties, improves objectivity when determining disease characteristics, and hastens the advancement of contemporary technology. In order to diagnose agricultural leaf illnesses, this study explores the most recent developments in deep learning methods, including CNN, DENSNET, InceptionV3, VGG16, Resnet50, and MobileNet, in addition to a variety of sensors. this project aims to aid scientists in the field by tackling challenges in merging deep learning and cutting-edge imaging tools to enhance illness identification. It addresses current trends and barriers, shedding light on unresolved issues and paving the way for further research. By clarifying persistent problems and posing new questions, it fosters progress and innovation in the field of medical imaging and diagnosis. © 2024 IEEE.

关键词： Contrastive Learning

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Approximation and Adaptive Equalization of RBF Neural Network in Nonlinear System 7

Approximation and Adaptive Equalization of RBF Neural Networ...

引用

7th international conference on Intelligent computing and Signal Processing, ICSP 2022

作者： Ren, Zhi-Yong Lin, Yu-Ke Chongqing College of Electronic Engineering School of Communication Engineering Chongqing China

ISBN: (纸本)9781665478571

In wireless communication system, the interference caused by time-varying and dynamic changes of nonlinear channel may lead to signal distortion and spectrum fading. A genetic algorithm based on decision feedback for adaptive neural network equalizer structure and error back propagation is proposed. the RBF neural network is used in the feedforward part of the equalizer to approximate the nonlinear system channel, the feedback part uses decision feedback based on the recursive least squares algorithm, which is used to quickly capture in the training phase and eliminate the residual inter-symbol interference caused by the feedforward equalizer. the mean square error convergence characteristic and the bit error rate fluctuation curve of the phase modulation signal after adaptive equalization are simulated, and the validity of the equalizer structure and algorithm is verified. the decision feedback RBF neural network adaptive equalizer can effectively eliminate the channel interference of the nonlinear system, and improve the performance of the equalizer in the steady state mean square error and bit error rate. © 2022 IEEE.

关键词： Radial basis function networks

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Internet of things based Accident Detection and Alerting System to Save Lives 7

Internet of Things based Accident Detection and Alerting Sys...

引用

7th international conference on Intelligent computing and Control Systems, ICICCS 2023

作者： Padmapriya, G. Krishnaswamy, R. Srinivasan, P. Pramila, P.V. SRM Institute of Science and Technology School of Computing Department of Computing Technologies Kattankulathur Campus Tamil Nadu Chennai India University College of Engineering Department of Electronics and Communication Engineering Tamil Nadu Ariyalur India Sona College of Technology Department of Electronics and Communication Tamil Nadu Salem India Saveetha School of Engineering Department Computer Science and Engineering Tamil Nadu Chennai India

ISBN: (纸本)9798350397253

More people are killed or injured in vehicle crashes every year. Delay in emergency preparedness is the primary cause of fatalities. the magic hour is the period immediately following a catastrophic event when critical medical and surgical attention raises the likelihood of maintaining a person's life by one on average. this study aimed to create an Internet of things (IoT)-based system for classifying and identifying accidents as an outcome. Before sending crucial crisis communications among healthcare personnel, the system can recognize and classifies automotive incidents based on their seriousness. A prompt and accurate assessment of the incident's extent is essential for enhancing the process approach's effectiveness and enabling rescue teams to precisely assess the resources needed. the suggested device starts working right away when an emergency status is identified. the application would initiate communication with the proper authorities and provide pertinent and essential information, such as the incident's location. To decide which machine learning algorithm was the most effective, the built system was also used to compare several types. © 2023 IEEE.

关键词： Internet of things

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High-order functional connectivity based Major depressive disorder classification using self-attention based CNN 7

High-order functional connectivity based Major depressive di...

引用

7th international conference on Data Science and Information technology, DSIT 2024

作者： Chenxi, Tian Meili, Lu Tianjin University of Technology and Education School of Information Technology Engineering Tianjin China

ISBN: (纸本)9798350384093

Major depressive disorder (MDD) is a common and socially significant psychiatric disorder with extremely complex pathologic mechanisms. In recent years, resting-state functional magnetic resonance imaging (rs-fMRI) has been widely used for the classification and diagnosis of MDD. Most current studies reveal the relationship between MDD and brain function by extracting static low-order functional connectivity (SFC) between brain regions, often neglecting potential high-order interactions that may affect classification performance. therefore, to fully exploit the more complex biomarker features between brain regions and enhance classification performance, this project extracts two types of dynamic high-order functional connectivity (dHOFC): dynamic topographic high-order functional connectivity (dthOFC) and dynamic associative high-order functional connectivity (daHOFC). It fuses the features of these two types of dynamic high-order functional connectivity and proposes a self-attention-based CNN method for MDD classification validation. the results demonstrate that the proposed deep learning algorithm achieves high classification performance, with the fusion of dthOFC and daHOFC features providing higher classification accuracy compared to using individual high-order functional connectivity features. © 2024 IEEE.

关键词： Deep learning

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Comprehensive Analysis of Tibetan Text Summarie 7

Comprehensive Analysis of Tibetan Text Summarie

引用

7th international conference on Machine Learning and Natural Language Processing, MLNLP 2024

作者： Norbu, Rinchen Tsoro Qunnuo Danzeng, Pubu Kyi, Lhamo Tibet University College of Information Science and Technology Lhasa850000 China National Local Joint Engineering Research Center for Tibetan Information Technology China

ISBN: (纸本)9798350354973

Text summarization has been rapidly developed as an important task in the field of natural language text generation. Among them, due to the practical needs of Tibetan text summarization, some people have also begun to engage in related research, but it is only in the beginning stage. the literature research method and analysis method are used to sort out the research and practical application of Tibetan text summarization in recent years and analyze the current status and problems of the current research on Tibetan text summarization for researchers' reference. © 2024 IEEE.

关键词： Generative adversarial networks

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the Preparation Method, Resistive Switching Mechanism and Application Prospects of Memristor 7

The Preparation Method, Resistive Switching Mechanism and Ap...

引用

7th international conference on Electrical, Mechanical and Computer engineering, ICEMCE 2023

作者： Li, Jiao Zhao, Ximei Lei, Tengfei Chai, Lin Wang, Shi Yu, Yuna Collaborative Innovation Center of Memristive and Computing Application Qilu Institute of Technology Jinan250200 China School of Intelligent Manufacturing and Control Engineering Qilu Institute of Technology Jinan250200 China College of Computer and Communication Engineering Qilu Institute of Technology Jinan250200 China

ISBN: (纸本)9798350382877

Memristors have also become one of the most promising research hotspots for solving data storage and computing problems faced in the big data era. As an emerging electronic device, memristor has potentially important applications in information storage and processing. this paper constructs a rod-shaped TiO2-x nanoscale memristor with FTO/TiO2-x/Cu structure, whose reliability is based on the memory behavior and its conversion mechanism. Research progress including materials, preparation methods, resistive switching mechanism and application prospects are described. First, the constituent materials of memristor are introduced, focusing on metal oxides and organic materials such as titanium oxide (TiO2). the choice of these materials is critical to memristor performance and applications. Secondly, the advantages and limitations of the preparation methods are discussed. then the resistance switching mechanism of memristor was studied in depth, focusing on the generation principle and adjustment mechanism of memristor effect. these include important concepts such as charge migration, Schottky barrier formation and oxygen vacancy drift, which help to understand the electrical properties of memristors. In addition, we explore the prospects of memristors in practical applications. Finally, past and current work in this field is summarized, and the prospects and challenges of memristorrelated research are prospected. © 2023 IEEE.

关键词： Memristors

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Research on Fog computing Task Scheduling Strategy with Deadline Constraints 7

Research on Fog Computing Task Scheduling Strategy with Dead...

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7th IEEE Advanced Information technology, Electronic and Automation Control conference, IAEAC 2024

作者： Liu, Lindong Wu, Yiling Guangdong University of Education School of Computer Science Guangzhou China

ISBN: (纸本)9798350339161

the task scheduling problem in Fog computing environments generally studies the scheduling strategy between tasks and computing resources, seeking a solution based on task scheduling execute time and performance optimization. there is little research on task scheduling strategies with deadline constraints. Based on the improved Apriori algorithm and utilizing the obtained task scheduling classification rules, this paper designs and proposes a task scheduling model and DLCM algorithm that meet time constraints in Fog computing environment. the DLCM algorithm was validated through simulation experiments, and compared to similar algorithms, the algorithm showed significant improvements in task execution time and scheduling costs. © 2024 IEEE.

关键词： Fog computing

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