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Showing 1 - 20 results of 153 for search '(( relevant data algorithm ) OR ((( image modeling algorithm ) OR ( data boosting algorithm ))))', query time: 0.14s Refine Results
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    Boosting the visibility of services in microservice architecture by Ahmet Vedat Tokmak (17773479)

    Published 2023
    “…Our research also analyzed the boosting algorithms, namely Gradient Boost, XGBoost, LightGBM, and CatBoost to improve the overall performance. …”
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    A machine learning model for early detection of diabetic foot using thermogram images by Amith Khandakar (14151981)

    Published 2021
    “…A comparatively shallow CNN model, MobilenetV2 achieved an F1 score of ∼95% for a two-feet thermogram image-based classification and the AdaBoost Classifier used 10 features and achieved an F1 score of 97%. …”
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    Variable Selection in Data Analysis: A Synthetic Data Toolkit by Mitra, Rohan

    Published 2024
    “…Variable (feature) selection plays an important role in data analysis and mathematical modeling. This paper aims to address the significant lack of formal evaluation benchmarks for feature selection algorithms (FSAs). …”
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    article
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    Artificial intelligence-based methods for fusion of electronic health records and imaging data by Farida Mohsen (16994682)

    Published 2022
    “…<div><p>Healthcare data are inherently multimodal, including electronic health records (EHR), medical images, and multi-omics data. …”
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    A Data-Driven Decision-Making Framework for Fleet Management in the Government Sector of Dubai by ALGHANEM, HANI SUBHI MOHD

    Published 2024
    “…Data-driven decision-making has become increasingly widespread and relevant across all business areas, including private and public sectors. …”
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    UniBFS: A novel uniform-solution-driven binary feature selection algorithm for high-dimensional data by Behrouz Ahadzadeh (19757022)

    Published 2024
    “…UniBFS exploits the inherent characteristic of binary algorithms-binary coding-to search the entire problem space for identifying relevant features while avoiding irrelevant ones. …”
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    A Survey of Audio Enhancement Algorithms for Music, Speech, Bioacoustics, Biomedical, Industrial, and Environmental Sounds by Image U-Net by Sania Gul (18272227)

    Published 2023
    “…Different than other published reviews, this review focuses entirely on AE techniques based on image U-Nets. We will discuss the need for AE, U-Net comparison to other DNNs, the benefits of converting the audio to 2D, input representations that are useful for different AE applications, the architecture of vanilla U-Net and the pre-trained models, variations in vanilla architecture incorporated in different E models, and the state-of-the-art AE algorithms based on U-Net in various applications. …”
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    Image-Based Air Quality Estimation Using Convolutional Neural Network Optimized by Genetic Algorithms: A Multi-Dataset Approach by Arshad Ali Khan (23152516)

    Published 2025
    “…This paper proposes a new approach using convolutional neural networks with genetic algorithms for estimating air quality directly from images. …”
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    Auto-indexing Arabic texts based on association rule data mining. (c2015) by Rouba G. Nasrallah

    Published 2015
    “…Our model denotes extracting new relevant words by relating those chosen by the previous classical methods, to new words using data mining rules. …”
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    masterThesis
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    A Fast and Robust Gas Recognition Algorithm Based on Hybrid Convolutional and Recurrent Neural Network by Xiaofang Pan (1895950)

    Published 2019
    “…The reported accuracy dramatically outperforms the previous algorithms, including gradient tree boosting (GTB), random forest (RF), support vector machine (SVM), k-nearest neighbor (KNN), and linear discriminant analysis (LDA). …”
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    Salak Image Classification Method Based Deep Learning Technique Using Two Transfer Learning Models by Theng, Lau Wei

    Published 2022
    “…Deep learning is the most promising algorithm compared to another Machine Learning (ML) algorithm. …”
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    Predicting Dropouts among a Homogeneous Population using a Data Mining Approach by BILQUISE, GHAZALA

    Published 2019
    “…Our research relies solely on pre-college and college performance data available in the institutional database. Our research reveals that the Gradient Boosted Trees is a robust algorithm that predicts dropouts with an accuracy of 79.31% and AUC of 88.4% using only pre-enrollment data. …”
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