Showing 61 - 80 results of 113 for search 'data (segmentations OR (documentation OR augmentation)) algorithm', query time: 0.09s Refine Results
  1. 61

    Blue collar laborers’ travel pattern recognition: Machine learning classifier approach by Aya Hasan Alkhereibi (17151070)

    Published 2021
    “…A pattern recognition model is applied to a revealed preference (RP) survey obtained from the Ministry of Transportation and Communication (MoTC) in Qatar for the travel diary for blue-collar workers. Raw data preprocessing and outliers detection and filtering algorithms were applied at the first stage of the analysis, and consequently, an activity-based travel matrix was developed for each household. …”
  2. 62

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

    Published 2019
    “…The road network is represented as a directed graph in which nodes are junctions (intersections) and edges are road segments. We assume that the city has deployed high-fidelity sensors for speed reading in a subset of edges; and the objective is to infer the speed readings for the remaining edges in the network; and to estimate the missing values in the segments for which sensors have stopped generating data due to technical problems (e.g., battery, network, etc.). …”
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    Deepfakes Signatures Detection in the Handcrafted Features Space by Hamadene, Assia

    Published 2023
    “…In the Handwritten Signature Verification (HSV) literature, several synthetic databases have been developed for data-augmentation purposes, where new specimens and new identities were generated using bio-inspired algorithms, neuromotor synthesizers, Generative Adversarial Networks (GANs) as well as several deep learning methods. …”
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  7. 67

    Prediction of Multiple Clinical Complications in Cancer Patients to Ensure Hospital Preparedness and Improved Cancer Care by Regina Padmanabhan (14231606)

    Published 2022
    “…Other highlights are (1) a novel set of easily available features for the prediction of the aforementioned clinical complications and (2) the use of data augmentation methods and model-scoring-based hyperparameter tuning to address the problem of class disproportionality, a common challenge in medical datasets and often the reason behind poor event prediction rate of various predictive models reported so far. …”
  8. 68

    A Comprehensive Overview of the COVID-19 Literature: Machine Learning–Based Bibliometric Analysis by Alaa Abd-Alrazaq (17430900)

    Published 2021
    “…It can be further scaled (for instance, in time) to clinical summary documentation. Publishers should avoid noise in the data by developing a way to trace the evolution of individual publications and unique authors.…”
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    Scan Test Cost and Power Reduction Through Systematic Scan Reconfiguration by Al-Yamani, A.

    Published 0000
    “…This paper presents segmented addressable scan (SAS), a test architecture that addresses test data volume, test application time, test power consumption, and tester channel requirements using a hardware overhead of a few gates per scan chain. …”
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    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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    Local convexity preserving rational cubic spline curves by Sarfraz, M.

    Published 1997
    “…An algorithm is presented which constructs a curve by interpolating the given data points. …”
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    A Novel Encryption Method for Dorsal Hand Vein Images on a Microcomputer by M. Z. Yildiz (16855476)

    Published 2019
    “…These were subjected to two different processes called contrast enhancement and segmentation of vein regions. Second, the pre- and post-processed images were encrypted with a new encryption algorithm in the microcomputer environment. …”