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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201-210 订阅

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A Close Look into Human Activity Recognition Models using Deep learning 3

A Close Look into Human Activity Recognition Models using De...

引用

3rd international conference on Computing, Networks and Internet of Things, CNIOT 2022

作者： Tee, Wei Zhong Dave, Rushit Seliya, Jim Vanamala, Mounika Major University of Wisconsin-Eau Claire Undergraduate Computer Science Eau ClaireMI United States University of Wisconsin-Eau Claire Computer Science Dept Eau ClaireMI United States

ISBN: (纸本)9781665469104

Human activity recognition using deep learning techniques has become increasing popular because of its high effectivity with recognizing complex tasks, as well as being relatively low in costs compared to more traditional machine learning techniques. This paper surveys some state-of-the-art human activity recognition models that are based on deep learning architecture and has layers containing Convolution Neural Networks (CNN), Long Short-Term Memory (LSTM), or a mix of more than one type for a hybrid system. The analysis outlines how the models are implemented to maximize its effectivity and some of the potential limitations it faces. Keywords: Human Activity Recognition, Deep learning © 2022 IEEE.

关键词： Long short-term memory

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machine learning based Intelligent Health Monitoring System 3

Machine Learning based Intelligent Health Monitoring System

引用

3rd international conference on Intelligent Engineering and Management, ICIEM 2022

作者： Ainapure, Bharati Patrikar, Prajakta Mehta, Aanchal Jain, Aniket Shah, Sanika Vishwakarma University Department of Computer Pune India

ISBN: (数字)9781665467568

ISBN: (纸本)9781665467568

In today's unprecedented time, it is essential to stay one step ahead in the field of healthcare as well as health intelligence by detecting and determining health related problems beforehand and taking swift decisions. However, due to a hectic schedule, it is not always possible for people to go to a medical appointment in person. This may cause therapy to be delayed, and it may eventually become the source of serious health problems. Proposed machine learning based health monitoring system is an android-based smart application that will not only assist users in identifying an illness based on symptoms but will also allow them to communicate with a professional. When a patient enters his or her symptoms, the system uses machine learning and deep learning algorithms to diagnose the illness. The system will offer a list of doctors who specialize in similar conditions based on the disease that has been diagnosed. Users can also arrange an appointment with a doctor at a time and date that is convenient for them. Procuring consultations by utilizing the chatting is also possible. © 2022 IEEE.

关键词： Data mining

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Impact of machine learning in Digital Marketing applications 3

Impact of Machine Learning in Digital Marketing Applications

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3rd international Informatics and Software Engineering conference, IISEC 2022

作者： Gursoy, Gunes Varol, Asaf Varol, Serkan Maltepe University College of Engineering and Natural Sciences Dept. of Computer Engineering İstanbul Turkey The University of Chattanooga College of Engineering and Computer Science Dept. of Engineering Management and Technology ChattanoogaTN United States

ISBN: (数字)9781665459952

ISBN: (纸本)9781665459952

The devastating Covid 19 pandemic has shifted priorities in the business world to accommodate the new normal that the pandemic has caused. Digital marketing has become a necessity for corporations to keep up with the evolving needs of consumers. With the help of the emerging technologies, corporations have begun embracing tailored digital marketing applications that aim to attract and retain more consumers. The techniques or applications used by businesses to improve their marketing performance are consolidated and supported by artificial intelligence applications. In this study, we examine the significance of the marketing field and machine learning, as well as marketing techniques, artificial intelligence, and machine learning algorithms. As a result of the examinations, it has been shown how machine learning techniques and algorithms facilitate marketing processes, increase the profitability of businesses and it is very difficult to realize digital marketing without machine learning algorithms. © 2022 IEEE.

关键词： Marketing

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Research on the Impact of MALL on Oral English Blended learning under the Background of "Internet Plus Education" : - Taking "FiF Oral English Training System" of iFLYTEK as an Example 3

Research on the Impact of MALL on Oral English Blended Learn...

引用

3rd international conference on Education, Knowledge and Information Management, ICEKIM 2022

作者： Du, Xiaoxuan Dalian Neusoft University of Information School of Foreign Languages Dalian China

ISBN: (纸本)9781665416665

Under the background of "Internet Plus Education", the Internet plays a more important role in oral English learning. With the rapid development of technology, the machine-aided learning has developed from computer assisted language learning (CALL) to the stage of mobile assisted language learning (MALL). At the same time, blended learning, which combines online and face-to-face learning, is also widely adopted. This paper makes use of contrast tests to analyze the pretest and posttest result statistics, aiming to research on the impact of MALL on oral English blended learning. © 2022 IEEE.

关键词： computer aided instruction

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Prediction of rainfall-type debris flow in Jiangjiagou based on LSTM-Attention 3

Prediction of rainfall-type debris flow in Jiangjiagou based...

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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： Gao, Yuan Li, Yingna Kunming University of Science and Technology College of Faculty of Information Engineering and Automation Kunming China Key Laboratory of Computer Technology Application of Yunnan Province Kunming China

ISBN: (纸本)9781665459112

Through the neural network model, the rainfall-type debris flow in Jiangjiagou is predicted. Based on seven meteorological factors with time series characteristics, such as daily rainfall, previous effective rainfall, ground temperature, and humidity, which have been screened by features, the Jiangjiagou rainfall debris flow prediction and early warning model based on LSTM-Attention is constructed. The results show that: (1) LSTM-Attention model is 0.02 higher than that of the Attention-LSTM model, and the prediction effect is better. (2) The prediction accuracy of LSTM-Attention model for Jiangjiagou rainfall-type debris flow can reach 0.88, which is 0.05, 0.07, 0.04, 0.25, 0.13 higher than that of LSTM model, RNN model, RNN-Attention model, SVM model, and BP model, respectively. Research results: It provides a new idea and method for the prediction and research of rainfall-type debris flow, which can be referenced by scholars. © 2022 IEEE.

关键词： Long short-term memory

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machine learning in Student Health - A Review 3

Machine Learning in Student Health - A Review

引用

3rd international conference on Issues and Challenges in Intelligent Computing Techniques, ICICT 2022

作者： Gurusamy, Deivanai Chakrabarti, Prasun Chakkaravarthy, Midhun Lincoln University College Faculty of Computer Science and Multimedia Malaysia Itm Sls Baroda University Department of Computer Science and Engineering India

ISBN: (纸本)9781665482684

Students' health is an important research topic today because they are the cornerstone of our society. Researchers have used various technological breakthroughs to address schoolchildren's and college/university students' health issues, and machine learning is now frequently employed. However, to understand the efficacy of machine learning and progress in student health research, a concise review of the influence of machine learning on student health is required, which the paper provides. The paper's primary objective is to examine which of the students' health concerns are efficiently addressed by machine learning algorithms and the outcomes of the approaches. The paper also discusses what leads students to perform poorly in schools, colleges, and universities and if machine learning will improve student health in the future. The review findings can be helpful to researchers in moving forward with unaddressed health-related problems and other solutions concerning the student's health. © 2022 IEEE.

关键词： Students

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Predicting A New Hotel Rating System by Analysing UGC Content from Tripadvisor: machine learning application to Analyse Service Robots Influence 3

Predicting A New Hotel Rating System by Analysing UGC Conten...

引用

3rd international conference on Industry 4.0 and Smart Manufacturing (ISM)

作者： Calero-Sanz, Jorge Orea-Giner, Alicia Villace-Molinero, Teresa Munoz-Mazon, Ana Fuentes-Moraleda, Laura Rey Juan Carlos Univ Signal & Commun Theory & Telemat Syst & Comp Madrid Spain Tech Univ Madrid Dept Appl Math & Stat EIAE Madrid Spain Rey Juan Carlos Univ High Performance Res Grp OPENINNOVA Madrid Spain Univ Paris 1 Pantheon Sorbonne EIREST Paris France Rey Juan Carlos Univ Business Econ Madrid Spain Rey Juan Carlos Univ Ctr Univ Estudios Turist Madrid Spain

Industry 4.0 tools permit computerized creation measures, and Artificial Intelligence (AI) approaches are pivotal in investigating the travel industry. Applying these devices to decipher User Generated Content (UGC) is fundamental to understand better client's necessities, opinions, and assumptions regarding tourism services. Through this research, an exploratory analysis of results is developed through machine learning Models to understand better the role played by robot and traveler typologies on the rating given to hotels considering TripAdvisor reviews of 74 hotels. The purpose of this exploratory research is to develop a methodology focused on analyzing online reviews related to service robots in hotels using machine learning techniques to train the data collected from TripAdvisor. Preliminary results show a link between the hotel rating given in TripAdvisor and the robot typology implemented in hotels. (C) 2022 The Authors. Published by Elsevier B.V.

关键词： robot typology traveler TripAdvisor Rating machine learning

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Customer Evaluation And Profit Maximization Using machine learning for Offline Stores 3

Customer Evaluation And Profit Maximization Using Machine Le...

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3rd international conference on Intelligent Computing, Instrumentation and Control Technologies, ICICICT 2022

作者： Gopinath, Abhijith Joy, Aloysius Wilson, Joyal Saji, Shamjith Devasia, Jeethu V Vimal Jyothi Engineering College Department of Computer Science and Engineering Chemperi670632 India

ISBN: (数字)9781665410052

ISBN: (纸本)9781665410052

Proper planning is essential for a long-term business. This can be done by implementing proper marketing strategies from time to time. machine learning can play a key role in decision-making. machine learning can play a key role in decision-making. This paper proposes a systematic approach which can help offline stores target their customers and obtain maximum profit by using the clustering application of machine learning. It helps offline stores get the benefits of the latest technologies in their business. The initial step for this system is to analyse the acquired sales data based on the purchase history, which will be used to group the customers. K-Means clustering is used to segment customers. Later, the most preferred product of each cluster is determined, and the result of this can be used by the shopkeepers to analyse their business and make good decisions for the long life of the business. It can assist offline stores in finding different groups of customers rather than viewing the entire customer as a single unit. © 2022 IEEE.

关键词： Decision making

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

2022 3rd International Conference on Computer Vision, Image ...

引用

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

ISBN: (纸本)9781665459112

The proceedings contain 253 papers. The topics discussed include: testing the feasibility of quantizing the progress of stroke patients’ rehabilitation with a computer vision method;recognition of surface defects of aluminum profiles based on convolutional neural network;a novel generative adversarial network simulating the complementary structure of DNA genetic information;an improved lightweight method of convolutional neural network for face recognition;a calculation method for line-of-sight stable attitude of networked optical transceiver based on depth feedforward neural network;a grapevine virus disease detection method based on convolution neural network;a predict method of measuring equipment operation performance based on improved local weighted partial least squares;research on multi-scale network computer modeling based on mobile vendor management;and identification method of dress pattern drawing based on machine vision algorithm.

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A Study of Deep learning Models in Diagnosis and Prediction of Chronic Diseases 3

A Study of Deep Learning Models in Diagnosis and Prediction ...

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3rd international conference on Issues and Challenges in Intelligent Computing Techniques, ICICT 2022

作者： Begum, Sayyada Hajera Vidyullatha, P. Koneru Lakshmaiah Education Foundation Dept of Computer Science and Engineering A.P Vaddeswaram India

ISBN: (纸本)9781665482684

With the introduction of big data and its incredible advancement in image procurement devices, transformation of medical data into valuable knowledge has become an important challenge in the area of bioinformatics. The medical images procured require huge analysis and diagnosis of images using AI techniques like machine and Deep learning (ML, DL) that yields automated diagnosis solutions. Deep learning methods can provide optimized and precise solutions for medical image diagnosis and can be an important methodology for imminent health care applications. Deep learning in biomedical image classification, automated image classification can aid in effective and early treatment of various diseases thus reducing mortality and morbidity rate. This paper gives an introduction to Deep learning models and reviews some contemporary deep learning models and their application in detecting various diseases. © 2022 IEEE.

关键词： Image classification

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