Search alternatives:
augmentations » augmentation (Expand Search), segmentation (Expand Search), argumentation (Expand Search)
fragmentation » segmentation (Expand Search)
augmentations » augmentation (Expand Search), segmentation (Expand Search), argumentation (Expand Search)
fragmentation » segmentation (Expand Search)
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Augmented arithmetic optimization algorithm using opposite-based learning and lévy flight distribution for global optimization and data clustering
Published 2022“…This paper proposes a new data clustering method using the advantages of metaheuristic (MH) optimization algorithms. …”
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Towards Multimedia Fragmentation
Published 2006“…Database fragmentation is a process for reducing irrelevant data accesses by grouping data frequently accessed together in dedicated segments. …”
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K Nearest Neighbor OveRsampling approach: An open source python package for data augmentation
Published 2022“…This paper introduces K Nearest Neighbor OveRsampling (KNNOR) Algorithm — a novel data augmentation technique that considers the distribution of data and takes into account the k nearest neighbors while generating artificial data points. …”
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Oversampling techniques for imbalanced data in regression
Published 2024“…For tabular data we conducted a comprehensive experiment using various models trained on both augmented and non-augmented datasets, followed by performance comparisons on test data. …”
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The use of semantic-based predicates implication to improve horizontal multimedia database fragmentation
Published 2007“…We particularly discuss multimedia primary horizontal fragmentation and focus on semantic-based textual predicates implication required as a pre-process in current fragmentation algorithms in order to partition multimedia data efficiently. …”
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Efficient Approximate Conformance Checking Using Trie Data Structures
Published 2021“…We show how our algorithm supports the definition of a budget for alignment computation and also augment it with strategies for meta-heuristic optimization and pruning of the search space. …”
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KNNOR: An oversampling technique for imbalanced datasets
Published 2021“…The proposed technique called K-Nearest Neighbor OveRsampling approach (KNNOR) performs a three step process to identify the critical and safe areas for augmentation and generate synthetic data points of the minority class. …”
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Unsupervised Deep Learning for Classification Of Bats Calls Using Acoustic Data
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Machine Learning-Driven Prediction of Corrosion Inhibitor Efficiency: Emerging Algorithms, Challenges, and Future Outlooks
Published 2025“…At the same time, virtual sample augmentation and genetic algorithm feature selection elevate sparse data performance, raising k-nearest neighbor models from R<sup>2</sup> = 0.05 to 0.99 in a representative thiophene set. …”
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Machine learning and structural health monitoring overview with emerging technology and high-dimensional data source highlights
Published 2021“…A detailed analysis of the ML pipelines is provided, and the in-demand methods and algorithms are summarized in augmentative tables and figures. …”
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Privacy-Preserving Framework for Blockchain-Based Stock Exchange Platform
Published 2022“…Furthermore, to assess the overhead of the proposed privacy algorithms on the trading execution time, we conduct several experiments considering different anonymity levels <i>k</i> . …”
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Generative AI revolution in cybersecurity: a comprehensive review of threat intelligence and operations
Published 2025“…<p dir="ltr">Cyber threats are increasingly frequent in today’s world, posing challenges for organizations and individuals to protect their data from cybercriminals. On the other hand, Generative Artificial Intelligence (GAI) technology offers an efficient way to automatically address these issues with the help of AI models and algorithms. …”
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Barriers of Adopting Artificial Intelligence Tools in Engineering Construction Projects
Published 2023“…AI technologies often struggle with construction data's fragmentation, inconsistency, and confidentiality. …”
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Scatter search metaheuristic for homology based protein structure prediction. (c2015)
Published 2015“…Results obtained by our algorithm are compared with other homology modeling approaches as well as a pure ab-initio and a fragment based assembly approach. …”
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masterThesis