Showing 421 - 440 results of 526 for search '(((( test processing algorithm ) OR ( data models algorithm ))) OR ( elements method algorithm ))', query time: 0.12s Refine Results
  1. 421

    Multi-Model Investigation and Adaptive Estimation of the Acoustic Release of a Model Drug From Liposomes by Wadi, Ali

    Published 2019
    “…Then, the algorithm was used to process the five experimental datasets. …”
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  2. 422

    Evacuation of a highly congested urban city by El Khoury, John

    Published 2017
    “…As the evacuation route planning is computationally challenging, an evacuation scheduling algorithm was adopted to expedite the solution process. …”
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  3. 423

    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. …”
  4. 424
  5. 425

    Lung nodule classification utilizing support vector machines by Mousa, W.A.H.

    Published 2002
    “…We intend to automate the pre-processing detection process to further enhance the overall classification.…”
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    article
  6. 426

    Just-in-time defect prediction for mobile applications: using shallow or deep learning? by Raymon van Dinter (10521952)

    Published 2023
    “…In this research, we evaluate the performance of traditional machine learning algorithms and data sampling techniques for JITDP problems and compare the model performance with the performance of a DL-based prediction model. …”
  7. 427

    Diagnostic performance of artificial intelligence in detecting and subtyping pediatric medulloblastoma from histopathological images: A systematic review by Hiba Alzoubi (18001609)

    Published 2025
    “…Techniques (e.g., model ensembling and multimodal data integration) are needed for better multiclass classification. …”
  8. 428

    MLMRS-Net: Electroencephalography (EEG) motion artifacts removal using a multi-layer multi-resolution spatially pooled 1D signal reconstruction network by Sakib Mahmud (15302404)

    Published 2022
    “…Because the diagnosis of many neurological diseases is heavily reliant on clean EEG data, it is critical to eliminate motion artifacts from motion-corrupted EEG signals using reliable and robust algorithms. …”
  9. 429

    Automatic Recognition of Poets for Arabic Poetry using Deep Learning Techniques (LSTM and Bi-LSTM) by AL SHOUBAKI, HAMZA YOUNIS

    Published 2024
    “…We also explore a range of algorithms, including traditional classifiers and deep learning models, to determine and select the most suitable and accurate models of identifying poets' names from the verses. …”
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  10. 430

    StackDPPred: Multiclass prediction of defensin peptides using stacked ensemble learning with optimized features by Muhammad Arif (769250)

    Published 2024
    “…The proposed StackDPPred method improves the overall accuracy by 13.41% and 7.62% compared to existing DPs predictors iDPF-PseRAAC and iDEF-PseRAAC, respectively on validation test. Additionally, we applied the local interpretable model-agnostic explanations (LIME) algorithm to understand the contribution of selected features to the overall prediction. …”
  11. 431

    Vibration suppression in a cantilever beam using a string-type vibration absorber by Issa, Jimmy S.

    Published 2017
    “…The string is rigidly connected to the fixed end of the beam and through a spring and damper to a second point on the beam. The finite element method is used to model the system and a reduced order model is obtained through modal reduction performed on both the string and the beam. …”
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  12. 432

    An Infrastructure-Assisted Workload Scheduling for Computational Resources Exploitation in the Fog-Enabled Vehicular Network by Sorkhoh, Ibrahim

    Published 2020
    “…A Dantzig–Wolfe decomposition algorithm is proposed which yields to a master program solvable by the Barrier algorithm and subproblems solve...…”
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  13. 433
  14. 434

    A geographic information system method to generate long term regional solar radiation resource maps: enhancing decision-making by Sachin Jain (19161721)

    Published 2024
    “…Digital surface model data is used as an auxiliary variable to further scale down to 30 m resolution. …”
  15. 435

    Positive Unlabelled Learning to Recognize Dishes as Named Entity by TAREK, AIMAN

    Published 2019
    “…With the lack of labelled data, I try to overcome the cold start and avoid manual labelling by building a lookup table from a dictionary. …”
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  16. 436

    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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  17. 437

    Digital Image Watermarking Using Balanced Multiwavelets by Ghouti, L.

    Published 2006
    “…In this paper, a robust watermarking algorithm using balanced multiwavelet transform is proposed. …”
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  18. 438

    Precision nutrition: A systematic literature review by Daniel Kirk (17302798)

    Published 2021
    “…Therefore, we carried out a Systematic Literature Review (SLR) to provide an overview of where and how machine learning has been used in Precision Nutrition from various aspects, what such machine learning models use as input features, what the availability status of the data used in the literature is, and how the models are evaluated. …”
  19. 439

    EEG-Based Multi-Modal Emotion Recognition using Bag of Deep Features: An Optimal Feature Selection Approach by Muhammad Adeel Asghar (6724982)

    Published 2019
    “…Features extracted from the proposed BoDF model have considerably smaller dimensions. The proposed model achieves better classification accuracy compared to the recently reported work when validated on SJTU SEED and DEAP data sets. …”
  20. 440

    Predicting COVID-19 cases using bidirectional LSTM on multivariate time series by Ahmed Ben Said (14158926)

    Published 2022
    “…Unlike other forecasting techniques, our proposed approach first groups the countries having similar demographic and socioeconomic aspects and health sector indicators using K-means clustering algorithm. The cumulative case data of the clustered countries enriched with data related to the lockdown measures are fed to the bidirectional LSTM to train the forecasting model. …”