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coding algorithm » cosine algorithm (Expand Search), colony algorithm (Expand Search), scheduling algorithm (Expand Search)
element » elements (Expand Search)
anbs » abs (Expand Search), anas (Expand Search), ans (Expand Search)
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CNN and HEVC Video Coding Features for Static Video Summarization
Published 2022Get full text
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Automatic Video Summarization Using HEVC and CNN Features
Published 2022Get full text
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Precision nutrition: A systematic literature review
Published 2021“…As such, recent research has applied machine learning algorithms, tools, and techniques in precision nutrition for different purposes. …”
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Machine learning for predicting outcomes of transcatheter aortic valve implantation: A systematic review
Published 2025“…Most of the included studies focused on mortality prediction, utilizing datasets of varying sizes and diverse ML algorithms. The most employed ML algorithms were random forest, logistics regression, and gradient boosting. …”
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Get full text
Get full text
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Machine learning for predicting outcomes of transcatheter aortic valve implantation: A systematic review
Published 2025“…Most of the included studies focused on mortality prediction, utilizing datasets of varying sizes and diverse ML algorithms. The most employed ML algorithms were random forest, logistics regression, and gradient boosting. …”
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Content-Symmetrical Multidimensional Transpose of Image Sequences for the High Efficiency Video Coding (HEVC) All-Intra Configuration
Published 2025“…In the literature, many solutions have been proposed that apply mainly to two-pass encoding, bitrate control algorithms, and enhancements of locally decoded images in the motion-compensation loop. …”
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The Frontiers of Deep Reinforcement Learning for Resource Management in Future Wireless HetNets: Techniques, Challenges, and Research Directions
Published 2022“…Then, we provide a comprehensive review of the most widely used DRL algorithms to address RRAM problems, including the value- and policy-based algorithms. …”
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The role of Reinforcement Learning in software testing
Published 2023“…Different machine learning technique types such as supervised and unsupervised learning were utilized in software testing. However, for some complex software testing scenarios, neither supervised nor unsupervised machine learning techniques were adequate. …”
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Oversampling techniques for imbalanced data in regression
Published 2024“…For tabular data, we also present the Auto-Inflater neural network, utilizing an exponential loss function for Autoencoders. …”
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Developing an online hate classifier for multiple social media platforms
Published 2020“…We then experiment with several classification algorithms (Logistic Regression, Naïve Bayes, Support Vector Machines, XGBoost, and Neural Networks) and feature representations (Bag-of-Words, TF-IDF, Word2Vec, BERT, and their combination). …”