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

共 1863 条记录，以下是241-250 订阅

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On the Development of Mobile application Breathing Analyzer to Detect Breathing Abnormalities 3

On the Development of Mobile Application Breathing Analyzer ...

引用

3rd international conference on Intelligent Data Science Technologies and applications, IDSTA 2022

作者： Hall, Dylan Gladdney, Anthony Labriny, Yasimine Alqudah, Yazan A University of West Florida Electrical and Computer Engineering PensacolaFL32514 United States

ISBN: (数字)9781665499606

ISBN: (纸本)9781665499606

This work presents a solution to monitor breathing patterns to detect any signs of abnormalities and ensure properly ventilating pulmonary system. The solution includes the ability to track and detect coughing. The system can be used by individuals to monitor breathing or athletes to monitor performance while exercising. The solution utilizes machine learning algorithms implemented through Edge Impulse to classify and analyze breathing patterns. It also features a user mobile application to record and transmit data and receive the classification results. © 2022 IEEE.

关键词： machine learning

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Personalized Federated learning with Data Heterogeneity Constraints 3

Personalized Federated Learning with Data Heterogeneity Cons...

引用

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

作者： Lin, Junke Wu, Xiangjun Henan University School of Computer and Information Engineering Kaifeng China Henan University School of Software Kaifeng China

ISBN: (纸本)9798350320404

Federated learning, a new distributed, edge-device based machine learning paradigm that does not require the collection of raw data from the client and has a significant privacy protection effect. However, since the data distribution of each client is Noniid, it will lead to the degradation of the model performance. We propose a new personalization federated learning approach to alleviate this problem that uses base layer and personalization layer, In addition, we add a restriction that we use the degree of Noniid (DoN) to constrain the personalization layer training. The larger the DoN, the more we allow the local model personalization layer to deviate from the global model personalization layer. Further, we have experimentally demonstrated that our method is superior to the federated averaging algorithm. © 2022 IEEE.

关键词： learning systems

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

CIBDA 2022 - 3rd International Conference on Computer Inform...

引用

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

ISBN: (纸本)9783800758760

The proceedings contain 244 papers. The topics discussed include: a proposed Siamese convolutional neural network for fingerprint recognition;research of early warning of corporate financial crisis based on machine learning neural network;corporate influence analysis by integrating social network models;research named entity recognition based on transfer learning;classification of complex network based on improved hierarchical model;handwritten character recognition based on convolution neural network models;back propagation neural network based stroke prediction;design of a network storage system based on peer-to-peer network with supernode;hybrid Weibo tags and topic mining for user similarity model;stability analysis of power grid based on generative adversarial network;convolutional neural network for English character recognition;build a precision marketing prediction model for intelligent recommendation technology;application of text mining technology in power data prediction;research on used car transaction price and transaction cycle based on model fusion;and underwater wireless sensor networks trustworthiness evaluation using Monte Carlo simulation.

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Towards A machine learning Framework for Suicide Ideation Detection in Twitter 3

Towards A Machine Learning Framework for Suicide Ideation De...

引用

3rd international conference on Artificial Intelligence and Data Sciences, AiDAS 2022

作者： Lim, Yan Qian Lee, Ming Jie Loo, Yim Ling Universiti Tunku Abdul Rahman Department of Internet Engineering and Computer Science Selangor Malaysia

ISBN: (数字)9781665491648

ISBN: (纸本)9781665491648

A worldwide rise of number of individuals had been observed to commit suicide at young age since 2019. With emergence of digital technologies, more suicides attempts were seen to have been pre-communicated through social media posts before the attempts. As such, much initiatives had been conducted to detect communication of distress on social media which imply risks of suicide attempts or any related forms of self-harm. Such initiatives aim to predict the possibility of suicide attempts for prevention measures. This work proposes a framework for machine learning of suicide ideation detection in social media which will contribute to the prediction of possibility of suicide attempt in a social media post. The framework includes data acquisition, data annotation, data pre-processing, feature extraction, classification and performance evaluation of the machine learning model. Acquisition of social media post samples from Twitter is proposed for training and testing datasets through representational state transfer application programming interface. Manual annotation is conducted on the training datasets with different formulated suicide risks. Data pre-processing is done through natural language toolkit and performance evaluation through valence aware dictionary for sentiment reasoning. This work will be further extended with a web-based application for implementation and evaluation of the trained machine learning model. © 2022 IEEE.

关键词： Forecasting

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Federated learning with Blockchain: A Study of the Latest Decentralized Couple 3

Federated Learning with Blockchain: A Study of the Latest De...

引用

3rd IEEE international conference on Computing, Communication, and Intelligent Systems, ICCCIS 2022

作者： Faridi, Arman Rasool Hafeez, Aiman Masood, Faraz Aligarh Muslim University Department of Computer Science Aligarh India

ISBN: (纸本)9781665462006

Federated learning is a method for machine learning that avoids the need to move data by training an algorithm in parallel on a large number of edge devices or servers that hold copies of the training data in their own memory. Conventional decentralized approaches often assume that local data samples are equally distributed, whereas typical centralized machine learning techniques involve uploading all local datasets to a single server. Federated learning has flaws like privacy and insufficient data. Blockchain's rise offers a safe and effective method for Federated learning implementation. In this paper, the collaboration of Federated learning and blockchain is discussed. Then the possible applications that can be developed using federated learning and blockchain are discussed. Furthermore, the challenges and opportunities for collaboration between these technologies are explained. © 2022 IEEE.

关键词： Blockchain

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A Survey on Precision agriculture using machine learning 3

A Survey on Precision agriculture using Machine Learning

引用

3rd international conference on Power, Energy, Control and Transmission Systems, ICPECTS 2022

作者： Prabhu, D. Dilip, Golda SRM Institute of Science and Technology Faculty of Engineering and Technology Department of Computer Science and Engineering Vadapalani Campus Chennai India

ISBN: (纸本)9781665462754

In modern farming fidelity permits the precise application of information sources, such as toxicant, seed, manure, and effluent, at the precise moment of harvest in order to increase productivity and crop yields. Ranchers may readily determine the crops' range by tracking them using sensors that are collected from the fields, protecting the resources being used and reducing the impact of weeds on the environment. Most Indian ranchers use standard cultivating techniques to determine the crop yield that should be developed in order. In any event, the ranchers don't sacrifice crop productivity because it depends on the characteristics of the soil due to abiotic variables. This research suggestsa yield recommendation apparatus that encourages ranchers to select the appropriate crop to plant in their lands in this manner. selecting information about systems by machine. © 2022 IEEE.

关键词： Crops

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The Human Resources Development applications of machine learning in the View of Artificial Intelligence 3

The Human Resources Development Applications of Machine Lear...

引用

3rd IEEE international conference on computer and Communication Engineering Technology, CCET 2020

作者： Tian, Jing Yunnan Normal University Faculty of Education Kunming650500 China

ISBN: (数字)9781728188119

ISBN: (纸本)9781728188119

The reform of Human Resources Development (Hrd) is more obvious than before, which is brought by new technologies. Artificial Intelligence (AI) and smart education leading by the innovation of Hrd has become the inevitable trend of Hrd informatization. With the rise of educational big data, how to analysis the data for predicting accurately, is the new topic in artificial intelligence era. As an important branch of artificial intelligence, machine learning can meet the need of analysis and prediction of Hrd. Based on the analysis of the interaction between machine learning, smart education and Hrd, machine learning assisting Hrd was analyzed in terms of learner tracking, intelligent teaching assistant, learning support and evaluation, resource recommendation, and personalized adaptive learning. And the application path of Hrd was reshaped by machine learning in the view of artificial intelligence. © 2020 IEEE.

关键词： machine learning

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application of machine learning Techniques in Slope Failure Analysis 3

Application of Machine Learning Techniques in Slope Failure ...

引用

3rd IEEE international conference on Computing, Communication, and Intelligent Systems, ICCCIS 2022

作者： Biswal, Shatrujit Sahoo, Simanchal Sethi, Sudeep Ranjan Panda, Sameer Chelva, M.S. Das, Sameer Kumar Sahoo, Arun Kumar Pramanik, Jitendra Centurion University of Technology and Management Odisha India Karnatak Arts Science and Commerce College Karnataka Bidar India Bhubaneswar Biju Patnaik University of Technology Department of Computer Science and Engineering Odisha Rourkela India National Institute of Technology Rourkela Centurion University of Technology and Management Department of Mining Odisha India National Institute of Technology Rourkela Trident Academy of Technology Department of Mining Odisha Bhubaneswar India

ISBN: (纸本)9781665462006

With furtherance in the mining industry, accidents due to slope failure are getting frequent in mining sites. Slope instability being a complex process, it seriously threatens the miner's life and properties. The damage inflicted by slope failures in the recent past has pulled the attention of authorities toward implementing disaster risk reduction measures. This research work plays a dominant role in palliating the slope failure risk. The presented work demonstrates the potentiality of machine learning models in forecasting the stability of the slopes. We implemented the limit equilibrium method (LEM) in predicting the factor of safety (FOS) of the slip surfaces for the designed slope. With the application of machine learning (ML) models such as K nearest neighbours and Gaussian Naive Bayes, we further classified the slopes based on their degree of stability. The performance of ML models is examined and compared through quality metric parameters like accuracy and confusion matrix. © 2022 IEEE.

关键词： Safety factor

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Skin Cancer Detection Using machine learning: A Survey 3

Skin Cancer Detection Using Machine Learning: A Survey

引用

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

作者： Desai, Ruchi Panchal, Juiee Mitra, Anjali Mamlekar, Shukur Chari, Harsha Aswale, Shailendra SRIEIT Goa University Computer Engineering Goa India

ISBN: (数字)9781665467568

ISBN: (纸本)9781665467568

Skin Cancer is one of the hazardous types of cancer. It is basically an unusual growing of skin cells which mostly develops on skin contact with the sun. Nowadays it also develops on areas of the skin which is not in contact to sunlight. It is essential to detect cancer at prior or else it tends to gradually spread over the other parts of the body. Here we present numerous machine learning techniques that are used to identify various types of cancer and classify whether it is Malignant or Benign. There are four main steps included in the process namely Preprocessing, Segmentation, Feature Extraction and Classification. The Paper concentrates on the comparison of different types of methods which can be used for the above steps. © 2022 IEEE.

关键词： machine learning

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Diabetic retinopathy detection using a pretrained machine learning model 3

Diabetic retinopathy detection using a pretrained machine le...

引用

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

作者： Sbai, Asma Touil, Abdelali Oukhouya, Lamya Cady Ayyad University Laboratory of Bioscience and Health Faculty of Medecine and Pharmacy of Marrakech Marrakech Morocco Faculty of Sciences Ibn Zohr University Laboratory of Engineering Sciences Agadir Morocco Ibn Zohr University Laboratory LIMA ENSA Agadir Agadir Morocco

ISBN: (数字)9781665457231

ISBN: (纸本)9781665457231

One of the possible side effects of diabetes is Diabetic Retinopathy. Early diagnosis of diabetic retinopathy is an important step toward healing and can prevent many patients from potential blindness. To identify diabetic retinopathy, practitioners may need an artificial intelligence tool to provide a second opinion to confirm or refute a diagnosis. In this article we use a pretrained machine learning model to find a solution to the issue of low-quality inputs by implementing, in the pre-processing step, the technique of Contrast Limited Adaptive Histogram Equalization to extract more features especially the blood vessels. © 2022 IEEE.

关键词： computer aided diagnosis

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