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检索条件"任意字段=Proceedings of the 2023 4th International Conference on Machine Learning and Computer Application"

共 4166 条记录，以下是21-30 订阅

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Fusion of data dimensionality reduction algorithms baced on category representation theory 4

Fusion of data dimensionality reduction algorithms baced on ...

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4th international conference on computer Vision, application, and Algorithm, CVAA 2024

作者： Xu, Xiaoxiang Li, Fanzhang Zhang, Li School of Computer Science and Technology Joint International Research Laboratory of Machine Learning and Neuromorphic Computing Provincial Key Laboratory for Computer Information Processing Technology Soochow University Suzhou China

ISBN: (纸本)9781510687615

For a long time, people have believed that representation problems are one of the bottlenecks in the field of machine learning. therefore, it is a long-term and exploratory work to study machine learning representation methods. Due to this, we use category theory to study the fusion representation of data dimensionality reduction. We propose the basic concept of category representation for data dimensionality reduction and provide a data dimensionality reduction fusion representation framework. We have conducted research and analysis on algorithms such as PCA, KPCA, and LDA, identified the essential connection between PCA, KPCA, and LDA and proposed a data dimensionality reduction fusion representation algorithm based on a data dimensionality reduction fusion representation framework. Finally, we demonstrated the feasibility of the proposed method through experiments. © 2025 SPIE.

关键词： Dimensionality reduction

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Deep learning for deepfake detection: Scientific landscape and future directions 4th

Deep learning for deepfake detection: Scientific landscape a...

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4th international conference on Computational Methods in Science and Technology, ICCMST 2024

作者： Dhiman, Pummy Kaur, Amandeep Sharma, Dilip Kumar Chitkara University Institute of Engineering and Technology Chitkara University Punjab India Department of Computer Engineering and Application GLA University Mathura India

ISBN: (纸本)9781032911571

In today’s digital age, technology has advanced to the point where it is difficult to distinguish be-tween genuine and forged media content. It was intended to be used for entertainment, but it is now being used to deceive people and create biasness, which can lead to disastrous situations. the goal of this bibliometric study is to provide scientific mapping on the role of deep learning in deepfake detection published online. Scopus and VOSviewer are used to create a concept map of 128 articles. Additionally, future directions for research are suggested. © 2025 the Author(s).

关键词： Fake detection

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A Deep learning Based System to Predict the Plant Disease Using Streamlit 4

A Deep Learning Based System to Predict the Plant Disease Us...

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4th international conference on Sentiment Analysis and Deep learning, ICSADL 2025

作者： Warbhe, Mohan K. Bore, Joy Jordan Chaudari, Shiv Nath Faculty of Engineering and Technology Department of Computer Science and Design Maharashtra Sawangi Wardha442001 India Faculty of Engineering and Technology Department of Computer Science and Medical Engineering MaharashtraSawangi Wardha442001 India

ISBN: (纸本)9798331523923

the proposed web application for tomato leaf disease detection exemplifies the transformative power of Artificial Intelligence and computer Vision in modern agriculture. Addressing the critical issue of early and accurate disease detection, this solution bridges the gap between advanced technological innovations and the practical needs of farming. the application is designed using Streamlit and Python to combine the usability of a friendly interface with the power of robust analytical capabilities in CNN, offering real-time reliable diagnosis and actionable insights to farmers. this application provides the highest possible accuracy and adaptability through the thorough training and evaluation of models and is a good asset for disease management. Deployment on scalable cloud platforms ensures access, reliability, and global reach. Future improvements, including extending disease detection to other crops, multilingual support, real-time recommendations, and integration with IoT devices, promise to expand its reach and utility. this initiative is a shining example of how AI-based solutions can transform agricultural practices by enhancing productivity, reducing losses, and ensuring sustainability. the application empowers farmers and contributes to a resilient agricultural ecosystem, addressing the pressing need for innovative and sustainable solutions in a rapidly evolving world. © 2025 IEEE.

关键词： Smart agriculture

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application of denoising diffusion probabilistic model in the minecraft environment 4

Application of denoising diffusion probabilistic model in th...

引用

4th international conference on computer Vision, application, and Algorithm, CVAA 2024

作者： Li, Sheng Macau University of Science and Technology China

ISBN: (数字)9781510687622

ISBN: (纸本)9781510687615

In this paper, we study the influence of hyperparameters of image generation model in Denoising Diffusion Probabilistic Model (DDPM) on image generation. Experiments were performed on MineRL dataset, the batch size, dimensions, learning rate, and sampling time steps of the model were adjusted, and the Fréchet Inception Distance (FID) was used to evaluate the quality of the resulting images. We introduce a performance degradation index to compare the effects of different hyperparameter settings. the experimental results show that dimension and learning rate are the key factors affecting the quality of DDPM image generation. these findings are of great significance for optimizing the DDPM model and improving its performance in image generation tasks. © 2025 SPIE.

关键词： Image denoising

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4th EAI international conference on Data Information in Online Environments, DIONE 2023

4th EAI International Conference on Data Information in Onli...

引用

4th EAI international conference on Data Information in Online Environments, DIONE 2023

ISBN: (纸本)9783031807121

the proceedings contain 21 papers. the special focus in this conference is on Data Information in Online Environments. the topics include: Deep Image Inpainting Incorporating Texture Prior Based on Gabor Filter;the Improved XdeepFM Algorithm Based on Attention Mechanism and Factorization machine;deep learning-Based Glaucoma Diagnostic Assistance System on Mobile Devices;using Alignment Chain to Boost Genetic Sequence Alignment Process;analysis of the Industrial Internet Industry Chain and Supply Capability Analysis of Key Links Within Jiangxi Province;a Lithium-Ion Battery Cathode Material Literature Entity Recognition Method Based on Deep learning;design and Implementation of Improved Multi-objective Genetic Algorithm Based on Uniform Distribution;Wavelet and Kalman Filter-Empowered Traffic Detection for Secure QUIC Network Communication;hyFed: A Hybrid Blockchain Empowered Federated learning Privacy Fair Framework;research on the Capability Status of Industrial Internet Security Supervision Platform;solar System Dynamics with Jet Propulsion Laboratory Ephemeris;elderly Health Care Data Integration Framework: Design and Implementation;challenges and Prospects of Power Network Security Protection in the Context of a New Power System: A Case Study of Jiangxi;enhancing Sequence Alignment Efficiency through Concurrent Utilization of Multiple Arm Processors in a Sequential Processing Framework;Fusion of Multiscale Convolution and LSTM for Stock Price Prediction;development of a Web application for the Sociocultural Diffusion of the Municipality of Lamas, Peru;A Solution Against Selective Jamming Attack in IEEE 802.15.4e Wireless Networks;TDFM and TAFM: Time-Aware and Feature Fusion-Based Deep Recommendation Models for Short Videos;blockchain Based Access Control: A Review and Future Perspectives.

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A distributed machine learning dynamic remote proof scheme that resists collusion attacks 4

A distributed machine learning dynamic remote proof scheme t...

引用

4th international conference on Network Communication and Information Security, ICNCIS 2024

作者： Wang, Ke Wu, Qiuxin Qin, Yu School of Applied Science Beijing Information Science and Technology University Beijing100192 China Trusted Computing and Information Assurance Laboratory Institute of Software Chinese Academy of Science Beijing100190 China

ISBN: (数字)9781510688261

ISBN: (纸本)9781510688254

Based on the security of distributed machine learning data and model based on remote proof, a cross-domain dynamic remote proof scheme based on ring signature improves the efficiency of computer cluster proof, the application of dynamic signature, realizes the real-time measurement of the confidence of computer cluster, and strengthens the real-time protection of data and model. computers with different security domain may adopt different remote proof mechanism, and convert the proof information of different proof methods into unified proof information, thus realizes the cross-domain dynamic remote proof between computer clusters. Noise is added when the cloud server distributes data to a distributed computer cluster. Due to the particularity of distributed architecture and the unsolution of indefinite equations, the enemy cannot conspire with one or more computers to steal data or the model parameters trained by endpoints. Finally, the safety of this method is verified through safety analysis and experimental analysis, and the computational overhead required in the proof process is reduced compared with other methods. © 2025 SPIE.

关键词： Authentication

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Vision-assisted applications based on deep learning 4

Vision-assisted applications based on deep learning

引用

4th international conference on computer Vision, application, and Algorithm, CVAA 2024

作者： Wang, Xingzheng Xi’an University of Electronic Science and Technology Xi’an710126 China

ISBN: (数字)9781510687622

ISBN: (纸本)9781510687615

With the rapid development of technology and the widespread application of deep learning, computer vision technology has become an important tool to help visually impaired people. Traditional visual assistance systems are often limited by recognition accuracy and real-time performance, while deep learning technology provides new ideas for the development of visual assistance applications with its powerful feature extraction and learning capabilities. this application is based on existing deep learning models and deploys object detection algorithms to mobile devices for user convenience by testing the system in actual environments. the intelligent voice interaction function provided by this application enhances the user experience and interaction sense. the application features are relatively complete, not only allowing users to select images from the album but also providing camera photography as input, as well as real-time content detection and output. At the same time, the application provides voice input and output, greatly simplifying the difficulty of user operation, and also facilitating users to obtain output and make corresponding judgments faster. this application provides a new visual aid tool for visually impaired individuals, making their lives more convenient. © 2025 SPIE.

关键词： Vision aids

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Unraveling Pulmonary Fibrosis Deep learning Transfer learning for Diagnosis 4

Unraveling Pulmonary Fibrosis Deep Learning Transfer Learnin...

引用

4th international conference on Sentiment Analysis and Deep learning, ICSADL 2025

作者： Rekha, G. Pongiannan, R.K. Pachipulusu, Venkata Sreeram Mogili, Sai Balaji Brindha, R. Maddileti, Telugu Srm Institute of Science and Technology Kattankulathur Dept. Computing Technologies Chennai603 203 India Srm Institute of Science and Technology Kattankulathur Computing Technologies Chennai603 203 India Guru Nanak Institutions Technical Campus Department of Electronics & Commn Engg Telangana Ibrahimpatnam501506 India

ISBN: (纸本)9798331523923

Pulmonary Fibrosis is a chronic lung disease demands prompt diagnosis for effective management. the proposed model develops an automated system using deep learning for feature extraction and machine learning for classification, reducing reliance on manual assessments. In the context, we use InceptionV3, VGG16, and MobileNetV2 for feature extraction as they are constantly successful and able to detect fine-grained patterns from medical images. the extracted features are further analyzed with popular machine learning techniques including but not limited to Random Forest and SVM. the proposed new hybrid model, leads to a faster diagnosis even if it is comparatively more accurate, than the previously used models. the system performance are evaluated using the accuracy, precision, recall, and F1-score. these are integrated into the Flask-based web application and it enables quick and accurate Pulmonary Fibrosis diagnosis, aiding timely treatment and better patient outcomes. © 2025 IEEE.

关键词： Lung cancer

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application of machine learning in port throughput prediction 4

Application of machine learning in port throughput predictio...

引用

4th international conference on computer Vision, application, and Algorithm, CVAA 2024

作者： Liu, Shulin Huang, Lei School of Economics and Management Beijing Jiaotong University Beijing China

ISBN: (数字)9781510687622

ISBN: (纸本)9781510687615

the rapid growth of global trade has made ports indispensable core nodes in the global logistics network. the study of port throughput has become a hot topic for modern researchers. this study focuses on Guangzhou Port Group, extracting its throughput data from 2014 to 2023 for preliminary time series analysis. By observing the autocorrelation and partial autocorrelation graphs based on monthly throughput data, we explored how port throughput is influenced by changes in industrial structure, the economic conditions of the hinterland, transportation capacity, and unexpected factors. Furthermore, through regression analysis, we identified key factors significantly impacting port throughput, including total import and export trade volume (in billions of RMB), total retail sales of consumer goods (in ten thousand RMB), waterway freight volume (in million tons), fixed asset investment growth rate (%), and overseas pandemic death tolls. Additionally, this study developed a combined RF-SVM-XGB port throughput prediction model, improving the average error by 3 percentage points. In terms of predictive performance and model error, the combined prediction model demonstrated better fitting accuracy. Finally, to enhance the model’s stability and generalization ability, cross-validation was used for result validation. Feasibility suggestions for port development were also provided. © 2025 SPIE.

关键词： Autocorrelation

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Task prioritization offloading scheme for vehicular edge computing networks: a game-theoretic DRL approach 4

Task prioritization offloading scheme for vehicular edge com...

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4th international conference on computer Vision, application, and Algorithm, CVAA 2024

作者： Sun, Jiaojiao Jiang, Li Cao, Yuwei Wang, Shubin Inner Mongolia University Huhehaote China

ISBN: (数字)9781510687622

ISBN: (纸本)9781510687615

With the development of Vehicular Edge Computing (VEC) computing architectures, in the study of task offloading problem, based on the differences in task delay sensitivity and the dynamic characteristics of environmental information, this paper designs a distributed DRL framework based on non-cooperative game, and introduces a memory mechanism (RNN) and a shared experience mechanism (Shared Experience Actor-Critic) in the MADDPG algorithm, which improves the learning efficiency of the algorithm as well as the convergence speed by capturing and sharing the time series data across time steps. © 2025 SPIE.

关键词： Deep reinforcement learning

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