Showing 181 - 200 results of 211 for search '(( elements method algorithm ) OR ((( data code algorithm ) OR ( data novel algorithm ))))', query time: 0.12s Refine Results
  1. 181

    Generic DFT approach for pattern sensitive faults in word-orientedmemories by Amin, A.A.

    Published 1996
    “…The testability problem of word-oriented memories (WOMs) for pattern sensitive faults is addressed. A novel design for testability (DFT) strategy allows efficient built-in self-testing (BIST) of WOMs. …”
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  2. 182
  3. 183

    A Survey of Deep Learning Approaches for the Monitoring and Classification of Seagrass by Uzma Nawaz (21980708)

    Published 2025
    “…This study not only examines the well-known challenges such as limited availability of data but provides a novel, structured taxonomy of deep learning techniques tailored for the monitoring of seagrass, highlighting their unique advantages and limitations within diverse marine environments. …”
  4. 184

    Copy number variations in the genome of the Qatari population by Khalid A. Fakhro (3158862)

    Published 2015
    “…Genotyping intensities and genome sequencing data from 97 Qataris were analyzed with four different algorithms and integrated to discover 16,660 high confidence CNV regions (CNVRs) in the total population, affecting ~28 Mb in the median Qatari genome. …”
  5. 185

    Sentiment Analysis for Arabic Social media Movie Reviews Using Deep Learning by MEZAHEM, FATEMA HAMAD

    Published 2022
    “…Prior to performing sentiment analysis, it is necessary to prepare the data so that it may be used to train machine learning (ML) algorithms. …”
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  6. 186
  7. 187

    Deep Learning in the Fast Lane: A Survey on Advanced Intrusion Detection Systems for Intelligent Vehicle Networks by Mohammed Almehdhar (22046597)

    Published 2024
    “…We highlight the transition from traditional signature-based to anomaly-based detection methods, emphasizing the significant advantages of AI-driven approaches in identifying novel and sophisticated intrusions. Our systematic review covers a range of AI algorithms, including traditional ML, and advanced neural network models, such as Transformers, illustrating their effectiveness in IDS applications within IVNs. …”
  8. 188

    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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  9. 189

    Enhancing building sustainability: A Digital Twin approach to energy efficiency and occupancy monitoring by Aya Nabil Sayed (17317006)

    Published 2024
    “…The DT technology enabled the creation of accurate virtual representations of users' physical environment, facilitating the optimization of energy-intensive devices and systems. Our data-driven occupancy detection approach utilized Machine Learning (ML) algorithms to intelligently determine room occupancy, allowing for precise energy management based on real-time usage patterns. …”
  10. 190
  11. 191

    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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  12. 192
  13. 193

    Combining offline and on-the-fly disambiguation to perform semantic-aware XML querying by Tekli, Joe

    Published 2023
    “…Many efforts have been deployed by the IR community to extend freetext query processing toward semi-structured XML search. Most methods rely on the concept of Lowest Comment Ancestor (LCA) between two or multiple structural nodes to identify the most specific XML elements containing query keywords posted by the user. …”
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  14. 194

    DeepRaman: Implementing surface-enhanced Raman scattering together with cutting-edge machine learning for the differentiation and classification of bacterial endotoxins by Samir Brahim, Belhaouari

    Published 2025
    “…ConclusionWe present the effectiveness of DeepRaman, an innovative architecture inspired by the Progressive Fourier Transform and integrated with the scalogram transformation method, in classifying raw SERS Raman spectral data from biological specimens with unparalleled accuracy relative to conventional machine learning algorithms. …”
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  15. 195

    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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  16. 196

    Decision-level fusion for single-view gait recognition with various carrying and clothing conditions by Al-Tayyan, Amer

    Published 2017
    “…Gait samples are fed into the MPCA and MPCALDA algorithms using a novel tensor-based form of the gait images. …”
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  17. 197

    Using artificial bee colony to optimize software quality estimation models. (c2015) by Abou Assi, Tatiana Antoine

    Published 2016
    “…We validate our technique on data describing maintainability and reliability of classes in an Object-Oriented system. …”
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    masterThesis
  18. 198

    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. …”
  19. 199

    Lung-EffNet: Lung cancer classification using EfficientNet from CT-scan images by Rehan Raza (17019105)

    Published 2023
    “…The class imbalance issue was handled through multiple data augmentation methods to overcome the biases. …”
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