Showing 21 - 40 results of 59 for search '(( elements per algorithm ) OR ((( data encoding algorithm ) OR ( data lacking algorithm ))))', query time: 0.11s Refine Results
  1. 21

    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. …”
  2. 22

    A Robust Deep Learning Approach for Distribution System State Estimation with Distributed Generation by Kfouri, Ronald

    Published 2023
    “…Also, to evaluate the robustness of the algorithms, we test the neural network, without retraining it, on multiple scenarios with noisier data and bad data. …”
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    masterThesis
  3. 23

    An App for Navigating Patient Transportation and Acute Stroke Care in Northwestern Ontario Using Machine Learning: Retrospective Study by Ayman Hassan (14426412)

    Published 2024
    “…The data were distributed for training (35%), testing (35%), and validation (30%) of the prediction model.…”
  4. 24

    Competitive learning/reflected residual vector quantization for coding angiogram images by Mourn, W.A.H.

    Published 2003
    “…Medical images need to be compressed for the purpose of storage/transmission of a large volume of medical data. Reflected residual vector quantization (RRVQ) has emerged recently as one of the computationally cheap compression algorithms. …”
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    article
  5. 25

    Multidimensional Gains for Stochastic Approximation by Saab, Samer S.

    Published 2019
    “…The proposed algorithms here aim for per-iteration minimization of the mean square estimate error. …”
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    article
  6. 26

    Design and analysis of entropy-constrained reflected residual vector quantization by Mousa, W.A.H.

    Published 2002
    “…Residual vector quantization (RVQ) is a vector quantization (VQ) paradigm which imposes structural constraints on the encoder in order to reduce the encoding search burden and memory storage requirements of an unconstrained VQ. …”
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    article
  7. 27

    Plant disease detection using drones in precision agriculture by Ruben Chin (17725986)

    Published 2023
    “…Color-infrared (CIR) images are the most preferred data used and field images are the main focus. The machine learning algorithm applied most is convolutional neural network (CNN). …”
  8. 28

    On the complexity of multi-parameterized cluster editing by Abu-Khzam, Faisal

    Published 2017
    “…In other words, Cluster Editing can be solved efficiently when the number of false positives/negatives per single data element is expected to be small compared to the minimum cluster size. …”
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    article
  9. 29

    Efficient Seismic Volume Compression using the Lifting Scheme by Khene, M. F.

    Published 2000
    “…In addition, the lifting scheme offers: 1) a dramatic reduction of the required auxiliary memory, 2) an efficient combination with parallel rendering algorithms to perform arbitrary surface and volume rendering for interactive visualization, and 3) an easy integration in the parallel I/O seismic data loading routines. …”
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    article
  10. 30

    Sentiment Analysis of Dialectal Speech: Unveiling Emotions through Deep Learning Models by EZZELDIN, KHALED MOHAMED KHALED

    Published 2024
    “…Dialect Speech Sentiment Analysis is an evolutional field where machine learning algorithms are utilized to detect emotions in spoken language. …”
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    A Geometric-Primitives-Based Compression Scheme for Testing Systems-on-a-Chip by El-Maleh, Aiman H.

    Published 2001
    “…In this paper, it is assumed that an embedded core will be used to execute the decompression algorithm and decompress the test data.…”
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    article
  13. 33

    A geometric-primitives-based compression scheme for testingsystems-on-a-chip by El-Maleh, A.

    Published 2001
    “…In this paper, it is assumed that an embedded core will be used to execute the decompression algorithm and decompress the test data…”
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    article
  14. 34

    STEM: spatial speech separation using twin-delayed DDPG reinforcement learning and expectation maximization by Muhammad Salman Khan (7202543)

    Published 2025
    “…For stationary sources, the proposed system gives satisfactory performance in terms of quality, intelligibility, and separation speed, and generalizes well with the test data from a mismatched speech corpus. Its perceptual evaluation of speech quality (PESQ) score is 0.55 points better than a self-supervised learning (SSL) model and almost equivalent to the diffusion models at computational cost and training data which is many folds lesser than required by these algorithms. …”
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    Precision nutrition: A systematic literature review by Daniel Kirk (17302798)

    Published 2021
    “…However, a systematic overview of the state-of-the-art on the use of machine learning in Precision Nutrition is lacking. 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. …”
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    Query acceleration in distributed database systems by Haraty, Ramzi A.

    Published 2001
    “…Query optimization strategies aim to minimize the cost of transferring data across networks. Many techniques and algorithms have been proposed to optimize queries. …”
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    article
  20. 40

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

    Published 2019
    “…In this research, I focus on extracting food and dish names as a named entity. 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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