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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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conferenceObject -
283
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284
FoGMatch
Published 2019“…In this context, the notion of fog computing has been projected to furnish data analytics and decision-making closer to the IoT devices. …”
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masterThesis -
285
The Effectiveness of Supervised Machine Learning in Screening and Diagnosing Voice Disorders: Systematic Review and Meta-analysis
Published 2022“…<h3>Background</h3><p dir="ltr">When investigating voice disorders a series of processes are used when including voice screening and diagnosis. …”
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286
Cyberbullying Detection in Arabic Text using Deep Learning
Published 2023“…Cyberbullying involves the use of communication technology and data, including messages, photographs, and videos, to undertake aggressive negative actions to harm others. …”
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287
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288
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). …”
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289
A systematic review of recent advances in the application of machine learning in membrane-based gas separation technologies
Published 2024“…The fingerprinting and descriptors are two commonly approach for polymer featurization. In terms of algorithms, <u>neural networks</u> (NNs), random forest (RF), and gaussian process regression (GPR) are among the most extensively applied methods. …”
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290
Higher-order statistics (HOS)-based deconvolution for ultrasonic nondestructive evaluation (NDE) of materials
Published 1997“…However, the improved performance is achieved at the expense of higher computational complexity and data requirements.…”
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masterThesis -
291
The Impact of AI on Decision-Making in Educational Management: Benefits, Risks, and Ethical Concerns
Published 2024“…AI technologies offer significant advantages, such as data-driven insights, improved efficiency, and enhanced predictive capabilities, which can support educational leaders in making more informed decisions. …”
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292
EEG-Based Multi-Modal Emotion Recognition using Bag of Deep Features: An Optimal Feature Selection Approach
Published 2019“…The BoDF model achieves 93.8% accuracy in the SEED data set and 77.4% accuracy in the DEAP data set, which is more accurate compared to other state-of-the-art methods of human emotion recognition.…”
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293
Anomaly Detection Based Framework for Profile Monitoring
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doctoralThesis -
294
A multi-pretraining U-Net architecture for semantic segmentation
Published 2025“…The proposed approach makes advantage of data augmentation to generate newly synthesized images, which are subsequently processed using a watershed mask. …”
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295
Deep Reinforcement Learning for Resource Constrained HLS Scheduling
Published 2022“…The two main steps in HLS are: operations scheduling and data-path allocation. In this work, we present a resource constrained scheduling approach that minimizes latency and subject to resource constraints using a deep Q learning algorithm. …”
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masterThesis -
296
An XML Document Comparison Framework
Published 2001“…As the Web continues to grow and evolve, more and more information is being placed in structurally rich documents, XML documents in particular, so as to improve the efficiency of similarity clustering, information retrieval and data management applications. Various algorithms for comparing hierarchically structured data, e.g., XML documents, have been proposed in the literature. …”
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297
CNN feature and classifier fusion on novel transformed image dataset for dysgraphia diagnosis in children
Published 2023“…Dysgraphia is a neurological disorder that hinders the acquisition process of normal writing skills in children, resulting in poor writing abilities. …”
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298
Future Prediction of COVID-19 Vaccine Trends Using a Voting Classifier
Published 2021“…Multiple ML algorithms are used to improve decision-making at different aspects after forecasting. …”
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Video surveillance using deep transfer learning and deep domain adaptation: Towards better generalization
Published 2023“…Typically, they can (i) ease the training process, (ii) improve the generalizability of ML and DL models, and (iii) overcome data scarcity problems by transferring knowledge from one domain to another or from one task to another. …”
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A novel XML document structure comparison framework based-on sub-tree commonalities and label semantics
Published 2011“…XML similarity evaluation has become a central issue in the database and information communities, its applications ranging over document clustering, version control, data integration and ranked retrieval. Various algorithms for comparing hierarchically structured data, XML documents in particular, have been proposed in the literature. …”
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article