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Showing 121 - 140 results of 247 for search '(( element method algorithm ) OR ((( data relative algorithm ) OR ( image processing algorithm ))))', query time: 0.11s Refine Results
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    Design Optimization of Inductive Power Transfer Systems Considering Bifurcation and Equivalent AC Resistance for Spiral Coils by Alireza Namadmalan (16864236)

    Published 2020
    “…Equivalent AC resistance of spiral coils is modeled based on eddy currents simulations using Finite Element Method (FEM) and Maxwell simulator. Based on the FEM simulations, a new approximation method using separation of variables is proposed as a function of spiral coil's main parameters. …”
  4. 124

    A multi-pretraining U-Net architecture for semantic segmentation by Cagla Copurkaya (22502042)

    Published 2025
    “…In this research, we propose and evaluate a modified version of a deep learning algorithm called U-Net architecture for partitioning histopathological images. …”
  5. 125

    From low-cost sensors to high-quality data: A summary of challenges and best practices for effectively calibrating low-cost particulate matter mass sensors by Michael R. Giordano (9976173)

    Published 2021
    “…The methods for correcting and calibrating these biases and dependencies that have been used in the literature likewise range from simple linear and quadratic models to complex machine learning algorithms. Here we review the needs and challenges when trying to get high-quality data from low-cost sensors. …”
  6. 126

    IntruSafe: a FCNN-LSTM hybrid IoMT intrusion detection system for both string and 2D-spatial data using sandwich architecture by Moutaz Alazab (17730060)

    Published 2025
    “…The IoMT sector deals with valuable, confidential healthcare-related data and offers convenient, personalized healthcare services. …”
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    Building power consumption datasets: Survey, taxonomy and future directions by Yassine Himeur (14158821)

    Published 2020
    “…Furthermore, data collection platforms and related modules for data transmission, data storage and privacy concerns used in different datasets are also analyzed and compared. …”
  9. 129

    Single channel speech denoising by DDPG reinforcement learning agent by Sania Gul (18272227)

    Published 2025
    “…<p dir="ltr">Speech denoising (SD) covers the algorithms that suppress the background noise from the contaminated speech and improve its clarity. …”
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    Correlation Clustering with Overlaps by Fakhereldine, Amin

    Published 2020
    “…In other words, data elements (or vertices) will be allowed to be members in more than one cluster instead of limiting them to only one single cluster, as in classical clustering methods. …”
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    masterThesis
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    What are artificial intelligence literacy and competency? A comprehensive framework to support them by Thomas K.F., Chiu

    Published 2024
    “…We also identify five effective learning experiences to foster abilities and confidences, and suggest five future research directions: prompt engineering, data literacy, algorithmic literacy, self-reflective mindset, and empirical research.…”
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    article
  17. 137

    Learning Spatiotemporal Latent Factors of Traffic via Regularized Tensor Factorization: Imputing Missing Values and Forecasting by Abdelkader Baggag (16864140)

    Published 2019
    “…And while spatiotemporal data related to traffic is becoming common place due to the wide availability of cheap sensors and the rapid deployment of IoT platforms, the data still suffer some challenges related to sparsity, incompleteness, and noise which makes the traffic analytics difficult. …”
  18. 138

    Digital twin in energy industry: Proposed robust digital twin for power plant and other complex capital-intensive large engineering systems by Ahmad K. Sleiti (14778229)

    Published 2022
    “…Data-driven algorithms with capabilities to predict the system’s dynamic behavior still need to be developed. …”
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    Adaptive Secure Pipeline for Attacks Detection in Networks with set of Distribution Hosts by ALSHAMSI, SUROUR

    Published 2022
    “…The research work carried out, in relation to attack detection ensemble learning, mainly aims to increase the performance of machine learning algorithms by combining their results. …”
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