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检索条件"任意字段=3rd International Conference on Machine Learning and Computer Application, ICMLCA 2022"

共 1866 条记录，以下是161-170 订阅

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Prediction of Addiction to Social Media 3

Prediction of Addiction to Social Media

引用

3rd IEEE international conference on Electrical, computer and Communication Technologies: computer Science and Engineering, ICECCT 2019

作者： Valakunde, Nandakishor Ravikumar, Srinath Department of Computer Engineering Vishwakarma Institute of Technology Pune India

ISBN: (纸本)9781538681572

Social media addiction is a huge problem among the youth. Due to the outburst of various social media applications, people are getting addicted to social media. This application is designed to help people to realize their addictions and also to provide constructive results according to the inputs given. The application uses machine learning to predict the outcomes based on past data taken from surveys. © 2019 IEEE.

关键词： machine learning

来源：评论

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application of text mining technology in power data prediction 3

Application of text mining technology in power data predicti...

引用

2022 3rd international conference on computer Information and Big Data applications, CIBDA 2022

作者： Guo, Jian Guo, Wu College of Architecture and Civil Engineering Qiqihar University Qiqihar China College of Communication and Electronic Engineering Qiqihar University Qiqihar China

ISBN: (纸本)9783800758760

This paper analyses the main research methods of power text mining technology in detail, and discusses the research hotspots of power text named entity recognition and named entity relationship extraction based on machine learning and deep learning. On this basis, the limited Boltzmann machine is further used to predict the power data. The test results show that the analysis of power text features in this paper is accurate, can effectively analyse the key text information, and the prediction results meet the requirements. © VDE VERLAG GMBH - Berlin - Offenbach.

关键词： Character recognition

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Proceedings - 2022 3rd international conference on computer Science and Management Technology, ICCSMT 2022

Proceedings - 2022 3rd International Conference on Computer ...

引用

3rd international conference on computer Science and Management Technology, ICCSMT 2022

ISBN: (纸本)9798350320404

The proceedings contain 111 papers. The topics discussed include: design of food safety management information system for western restaurant;research on enterprises’ response to emergencies based on machine learning;design and application of crop variety recommendation and production decision system in agricultural production;research on network structure analysis of English learning in social media;research on the prediction of e-commerce platform user churn based on random forest model;gazetteer enhanced named entity recognition for musical user-generated content;an application study of stochastic service systems based on operations search;risk early warning and response of PPP projects in characteristic towns based on fuzzy group decision- making and matter-element model;design and realization of an online examination system based on maven framework;design and implementation of dynamic interactive e-book system;optimization method for cloud service composition of machine tools under multiple constraints;application of environmental monitoring and control system in agricultural production;and design and implementation of warehouse management system based on Vuetify 3.0 framework.

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The application of Graph Neural Network in Natural Language Processing and computer Vision 3

The Application of Graph Neural Network in Natural Language ...

引用

3rd international conference on machine learning, Big Data and Business Intelligence (MLBDBI)

作者： Liu, Xiaochen Su, Yang Xu, Bingjie Hubei Univ Technol Sch Comp Sci Wuhan Peoples R China Univ Waterloo Cheriton Sch Comp Sci Waterloo ON Canada Southwest Jiaotong Univ Sch Comp Sci & Artificial Intelligence Chengdu Peoples R China

ISBN: (纸本)9781665417907

Graphs can represent information transformation via geometrical relations, which have been well studied and applied in various research areas. A graph-based learning network named Graph Neural Network (GNN) arose with the vast development of deep learning in recent years. Unlike traditional deep learning networks such as CNN and RNN, GNN is superior in dealing with non-Euclidean graph data. This survey focuses on two widespread application fields of GNN, natural language processing (NLP) and computer vision (CV). Firstly, based on the tasks they perform, we categorize the most popular research sub-domains of NLP and CV, purpose a detailed review on the application of GNN in these areas. Secondly, we thoroughly analyzed the benchmark datasets applied in the GNN models while comparing them with different evaluation metrics. Finally, we briefly discuss the potential future direction of GNN according to its model building procedure and related application branches.

关键词： deep learning graph neural network natural language processing computer vision

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Human profiling based on computer vision : A survey with application 3

Human profiling based on computer vision : A survey with app...

引用

3rd IEEE international conference on Electronics, Control, Optimization and computer Science, ICECOCS 2022

作者： Elbaghazaoui, Bahaa Eddine Amnai, Mohamed Fakhri, Youssef Choukri, Ali Gherabi, Noreddine IbnTofail University Laboratory of Computer Sciences Faculty of Sciences Kenitra Kenitra Morocco Sultan Moulay Slimane University National School of Applied Sciences Khouribga Morocco

ISBN: (数字)9781665457231

ISBN: (纸本)9781665457231

machine learning is currently a prominent issue due to the direct training of machines with minimal human input. In the present period, the scenario of manual machine feeding has changed, it now learns automatically. machine learning approaches are utilized for a variety of tasks, such as feature extraction, pattern recognition, object recognition, and classification. In computer vision, machine learning is used to extract important information from visual data. computer vision contributes to a variety of disciplines, including surveillance, robotics, suspect detection, optical character recognition, and numerous other technologies. computer vision helps in extracting metadata from humans, such as emotions, sentiments, personality, and so on. This paper presents a thorough yet current survey of human profiling based on computer vision. However, we present a taxonomy of data profiling and computer vision as well as how to profile humans from image data. As an experience, we will discuss our program about human faces recognising emotions from a person's image using deep learning. In any event, the outcomes we have achieved are critical and important. © 2022 IEEE.

关键词： computer vision

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application of computer Vision and Deep learning in Breast Cancer Assisted Diagnosis 2019

Application of Computer Vision and Deep Learning in Breast C...

引用

3rd international conference on machine learning and Soft Computing (ICMLSC)

作者： Gu Yunchao Yang Jiayao Beihang Univ Sch Comp Sci & Engineer 37 Xueyuan Rd Beijing Peoples R China Xianyang Rainbow Middle Sch 1 Rainbow Rd Xianyang Shaanxi Peoples R China

ISBN: (纸本)9781450366120

In the general process of breast cancer diagnosis, doctors mainly analyze and judge B-mode ultrasound images through vision, which depends heavily on doctors' operational experience and technical level. Artificial intelligence methods represented by machine learning algorithms have made rapid progress in recent years, especially natural image classification, target detection, semantics segmentation based on computer vision technology have been relatively mature, and have been widely used successfully in various fields. So as to improve the automation ability and reduce human errors, etc. By using artificial intelligence technology such as computer vision and in-depth learning, an automated method is established to diagnose breast cancer B-mode ultrasound images. This method can quickly strengthen the correct diagnostic rate of front-line medical staff and reduce the difference of operation level between urban and rural doctors. It has obvious medical needs and wide social significance.

关键词： Ultrasound imaging Deep learning Convolution neural network Target detection

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Prediction of hospital stay for patients undergoing partial hip replacement surgery based on machine learning algorithms 3

Prediction of hospital stay for patients undergoing partial ...

引用

2023 IEEE 3rd international conference on Data Science and computer application, ICDSCA 2023

作者： Yao, Yi The Affiliated Hospital of Southwest Medical University Department of Anesthesiology Luzhou China

ISBN: (纸本)9798350341546

Partial hip replacement surgery is a common surgical method for treating severe hip joint diseases. Accurate prediction of the length of hospital stay for patients undergoing partial hip replacement surgery is of great significance for optimizing rehabilitation planning, resource utilization, surgical safety, and improving healthcare quality. Due to the complexity of factors involved in partial hip replacement, traditional clinical experience-based predictions have subjective limitations. This study aims to construct a predictive model for the length of hospital stay for patients undergoing partial hip replacement surgery based on clinical data using different machine learning algorithms. The performance of different algorithms was evaluated, and the results showed that the backpropagation neural network (BPNN) demonstrated good performance in predicting the length of hospital stay after partial hip replacement, providing accurate prediction results and decision support for healthcare teams. © 2023 IEEE.

关键词： backpropagation neural network length of hospital stay machine learning partial hip replacement predictive model

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Research on the application of Cloud Computing Technology in computer Data Processing 3

Research on the Application of Cloud Computing Technology in...

引用

3rd international conference on machine learning, Big Data and Business Intelligence (MLBDBI)

作者： Zhang, Jun Sichuan Judicial & Police Officers Profess Coll Deyang 618000 Sichuan Peoples R China

ISBN: (纸本)9781665417907

In the information age, advanced Internet technology and cloud computing technology have been widely used in all walks of life, which have brought great convenience to people's work and life. Cloud computing technology can not only provide a good platform for computer data processing, but also provide a platform for users to use cloud computing to process data and information, and provide security for data transmission. However, due to the particularity of the computer network environment and the characteristics of cloud computing technology, there are still some security issues that need to be resolved. This article will combine the related concepts and content of cloud computing technology to analyze the role and specific application of cloud computing technology in computer data processing. The author puts forward the problems existing in the application of current cloud computing technology. In order to better play the value of cloud computing technology in computer data processing, the author of this article has given effective measures to ensure cloud computing security, strengthen research and development of hybrid cloud computing, develop corresponding programs, and improve performance.

关键词： Cloud computing technology computer Data processing

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A Comparison between Using Fuzzy Cognitive Mapping and machine learning to Predict Students' Performance in Higher Education 3

A Comparison between Using Fuzzy Cognitive Mapping and Machi...

引用

3rd IEEE international conference on Electronics, Control, Optimization and computer Science, ICECOCS 2022

作者： Oqaidi, Khalid Aouhassi, Sarah Mansouri, Khalifa ENSET of Mohammedia University Hassan II of Casablanca Laboratory SSDIA Mohammedia Morocco

ISBN: (数字)9781665457231

ISBN: (纸本)9781665457231

Higher education quality (HEQ) stakeholders increasingly see the student as the core of the teaching operation. To improve HEQ a good prediction of students' performance is a considerable step. In this paper we discuss the use of two approaches used in the literature in students' performance (SP) prediction: machine learning (ML) techniques and Fuzzy Cognitive Mapping (FCM). Our main contribution is a comparative analysis of these approaches and recommendations in context of the Moroccan Higher Education institutions. © 2022 IEEE.

关键词： machine learning

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Capturing Temporal Information with LSTM to Stabilize A Rotating machine 3

Capturing Temporal Information with LSTM to Stabilize A Rota...

引用

3rd international conference on computer Vision, Image and Deep learning and international conference on computer Engineering and applications, CVIDL and ICCEA 2022

作者： Wei, Yaoyao Qu, Weiming Zhang, Tao Deng, Yian Hu, Fan Zhang, Xiangqi Liu, Tianlin Bolchover, Paul Yu, Tao Zheng, Guishui Zhang, Ping Liu, Qing Luo, Dingsheng Peking University School of Artificial Intelligence Beijing China Schlumberger

ISBN: (纸本)9781665459112

Rotor stability, which indicates the performance of a rotor keeping the system in good working order without transverse vibration, is one of the important research contents in rotor dynamics area. Actually, in a real working environment, it is difficult to stabilize a rotating machine because violent transverse vibrations often happen due to the influence of air resistance, ground friction, errors in manufacture of the rotor, and other factors. The vibrations not only cause instability of the system, but also greatly limit the increase of the rotational speed. We think that the temporal information of the rotating machine, which records the history of its motion, is useful to help reduce the vibrations and stabilize the rotating machine. A recurrent neural network architecture, Long Short-Term Memory (LSTM) is employed to capture the complex and changeable temporal information. So, in this research, an intelligent control approach, that is deep reinforcement learning coupled with LSTM capturing temporal information, is proposed to stabilize a rotating machine. Experimental results in simulation platform demonstrate the effectiveness and robustness of the approach. © 2022 IEEE.

关键词： Reinforcement learning

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