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Garbage classification using deep learning technologyGarbage classification has always been an important issue in environmental protection, resource recycling, and social livelihood. However, garbage classification takes a lot of time and effort.... Author: Ngo Huu-Huy, Bui Tung Van, Le Linh Hung, Nguyen Minh Duy Keyword: Artificial Intelligence; convolutional neural network; deep learning; garbage classification; machine learning.
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Improving the efficacy of network security based on dimensionality reduction techniquesThis paper focuses on proposing a network intrusion detection model applying fundamental machine learning techniques to enhance early detection of network intrusions (rapid detection of attack... Author: Phuong Hoang Thi Keyword: Network attack DDoS machine learning deep learning dimensionality reduction
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BiDAF model in sentiment analysis taskSentiment analysis is a critical job in natural language processing. Controlling and evaluating customer feedback on their goods is a task that companies are especially interested in. For reading... Author: Huế Lương Thị Minh Keyword: Natural language processing; LSTM; deep learning; machine learning; BiDAF.
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A systematic review of the application of artificial intelligence techniques in the development of smart wearable device applicationsThe convergence of artificial intelligence (AI) and wearables is ushering in a new paradigm of software development - AI-powered app creation - where AI is not just a feature but a software creation... Author: Dung Nguyen Thi, Nguyen Phuong Thu, Doan Phuong Ngoc Keyword: AI-powered wearable apps TinyML systematic review PRISMA guidelines software development for wearables
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Gradient descent method and parameter selection for image restoration problemImage enhancement is a meaningful problem in many practical applications. It plays an important role in preprocessing steps for recognition and information extraction. Image restoration is often... Author: Dũng Nguyễn Đình Keyword: Image restoration Gradient Descent iterative method convex optimization optimal parameter
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Overview study of mobile network traffic for BTS stationsIn recent years, Machine Learning (ML) has become a crucial and promising tool for forecasting and solving a wide range of complex problems. The rapid development of machine learning is closely linked... Author: Thuc Hoang Van, Thang Vu Chien, Nam Pham Thanh, Thao Doan Thi Thanh, Ngoc Pham Van, Phuong Mac Thi Keyword: 5G Traffic base station BTS for 5G Network 5G/BTS Traffic 5G Traffic
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Applying the Autoencoder model for URL phishing detectionIn the era of digital transformation, alongside the rapid devel-opment of the Internet and online applications, phishing at-tacks targeting users through malicious URLs have been in-creasingly... Author: Mai Dang Thi Keyword: URL Phishing detection Autoencoder latent space
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Developing a product rating prediction model based on customer text feedback using machine learning algorithmsThis study focuses on predicting product rating scores from customer text feedback. This task combines the challenges of natural language processing (NLP) with the class imbalance phenomenon commonly... Author: Ha Dien Thi Hong Keyword: Product rating prediction customer text feedback natural language processing (NLP) machine learning models model performance evaluation
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A study on machine learning-based approaches for early detection of Parkinson’s diseaseParkinson’s disease (PD) is a progressive neurodegenerative disorder characterized by the gradual loss of dopaminergic neurons in the brain, leading to both motor and non-motor symptoms. This study... Author: Huong Tran Thi Keyword: Parkinson’s Disease Early Diagnosis Machine Learning XGBoost Random Forest Clinical Data Analysis
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Machine learning-based methods for supporting fake news detectionIn the context of rapidly disseminating online information, fake news has emerged as a serious threat to information security and public trust. Traditional detection methods based on content analysis... Author: Anh Tran Thi Lan Keyword: Fake news detection hypergraph neural networks machine learning graph-based models HGFND
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