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Showing 321 - 340 results of 350 for search '(((( data mining algorithm ) OR ( data processing algorithm ))) OR ( element search algorithm ))', query time: 0.10s Refine Results
  1. 321
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    Future Prediction of COVID-19 Vaccine Trends Using a Voting Classifier by Syed Ali Jafar Zaidi (19563178)

    Published 2021
    “…Multiple ML algorithms are used to improve decision-making at different aspects after forecasting. …”
  3. 323

    Video surveillance using deep transfer learning and deep domain adaptation: Towards better generalization by Yassine Himeur (14158821)

    Published 2023
    “…While artificial intelligence (AI) smooths the path of computers to think like humans, machine learning (ML) and deep learning (DL) pave the way more, even by adding training and learning components. DL algorithms require data labeling and high-performance computers to effectively analyze and understand surveillance data recorded from fixed or mobile cameras installed in indoor or outdoor environments. …”
  4. 324

    Predicting and Interpreting Student Performance Using Machine Learning in Blended Learning Environments in a Jordanian School Context by SALIM, MAHA JAWDAT

    Published 0024
    “…These platforms enhance academic performance by fostering collaborative learning environments and generating extensive data from every user interaction. Machine learning algorithms can process large and complex datasets to identify patterns and trends that may not be immediately apparent. …”
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  5. 325

    Towards Multimedia Fragmentation by Saad, Samir

    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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  6. 326

    Overview of Artificial Intelligence–Driven Wearable Devices for Diabetes: Scoping Review by Arfan Ahmed (17541309)

    Published 2022
    “…WDs coupled with artificial intelligence (AI) algorithms show promise to help understand and conclude meaningful information from the gathered data and provide advanced and clinically meaningful analytics.…”
  7. 327

    CNN feature and classifier fusion on novel transformed image dataset for dysgraphia diagnosis in children by Jayakanth, Kunhoth

    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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  8. 328

    CNN feature and classifier fusion on novel transformed image dataset for dysgraphia diagnosis in children by Jayakanth Kunhoth (14158908)

    Published 2023
    “…<p dir="ltr">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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    An XML Document Comparison Framework by Tekli, Joe

    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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  11. 331

    A novel XML document structure comparison framework based-on sub-tree commonalities and label semantics by Tekli, Joe

    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
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    Cyberbullying Detection in Arabic Text using Deep Learning by ALBAYARI, REEM RAMADAN SA’ID

    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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  14. 334

    Single-Cell Transcriptome Analysis Revealed Heterogeneity and Identified Novel Therapeutic Targets for Breast Cancer Subtypes by Radhakrishnan Vishnubalaji (3563306)

    Published 2023
    “…In the current study, we employed computational algorithms to decipher the cellular composition of estrogen receptor-positive (ER<sup>+</sup>), HER2<sup>+</sup>, ER<sup>+</sup>HER2<sup>+</sup>, and triple-negative BC (TNBC) subtypes from a total of 49,899 single cells’ publicly available transcriptomic data derived from 26 BC patients. …”
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    The Impact of AI on Decision-Making in Educational Management: Benefits, Risks, and Ethical Concerns by JA’AROUN, WAED YOUSEF

    Published 2024
    “…However, the adoption of AI also presents challenges, including potential biases in algorithms, privacy concerns, and the risk of an over-reliance on automated systems. …”
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  17. 337

    Cyberbullying Detection Model for Arabic Text Using Deep Learning by Albayari, Reem

    Published 2023
    “…Hence, detecting any act of cyberbullying in an automated manner will be helpful for stakeholders to prevent any unfortunate results from the victim’s perspective. Data-driven approaches, such as machine learning (ML), par ticularly deep learning (DL), have shown promising results. …”
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  18. 338

    Enhancement of SAR Speckle Denoising Using the Improved Iterative Filter by Yahia, Mohamed

    Published 2020
    “…The recent advancement in synthetic aperture radar (SAR) technology has enabled high-resolution imaging capability that calls for efficient speckle filtering algorithms to preprocess radar imagery. Since the introduction of the Lee sigma filter in 1980, the various versions of the minimum mean square error (MMSE) filter were developed, focusing essentially on how to estimate the processed pixels. …”
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  19. 339

    Diagnostic test accuracy of AI-assisted mammography for breast imaging: a narrative review by Daksh Dave (17949239)

    Published 2025
    “…Artificial intelligence (AI), with its ability to process vast amounts of data and detect intricate patterns, offers a solution to the limitations of traditional mammography, including missed diagnoses and false positives. …”
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