يعرض 61 - 65 نتائج من 65 نتيجة بحث عن '(( binary b model optimization algorithm ) OR ( binary tasks based optimization algorithm ))', وقت الاستعلام: 0.38s تنقيح النتائج
  1. 61

    Quadratic polynomial in 2D image plane. حسب Indhumathi S. (19173013)

    منشور في 2024
    "…<div><p>Feature description is a critical task in Augmented Reality Tracking. This article introduces a Convex Based Feature Descriptor (CBFD) system designed to withstand rotation, lighting, and blur variations while remaining computationally efficient. …"
  2. 62

    Data_Sheet_1_Multiclass Classification Based on Combined Motor Imageries.pdf حسب Cecilia Lindig-León (7889777)

    منشور في 2020
    "…In this way, for each binary problem, the CSP algorithm produces features to determine if the specific body part is engaged in the task or not. …"
  3. 63

    Supplementary Material 8 حسب Nishitha R Kumar (19750617)

    منشور في 2025
    "…</li><li><b>XGboost: </b>An optimized gradient boosting algorithm that efficiently handles large genomic datasets, commonly used for high-accuracy predictions in <i>E. coli</i> classification.…"
  4. 64

    Table 1_Heavy metal biomarkers and their impact on hearing loss risk: a machine learning framework analysis.docx حسب Ali Nabavi (21097424)

    منشور في 2025
    "…Multiple machine learning algorithms, including Random Forest, XGBoost, Gradient Boosting, Logistic Regression, CatBoost, and MLP, were optimized and evaluated. …"
  5. 65

    Machine Learning-Ready Dataset for Cytotoxicity Prediction of Metal Oxide Nanoparticles حسب Soham Savarkar (21811825)

    منشور في 2025
    "…</p><p dir="ltr">Encoding: Categorical variables such as surface coating and cell type were grouped into logical classes and label-encoded to enable model compatibility.</p><p dir="ltr"><b>Applications and Model Compatibility:</b></p><p dir="ltr">The dataset is optimized for use in supervised learning workflows and has been tested with algorithms such as:</p><p dir="ltr">Gradient Boosting Machines (GBM),</p><p dir="ltr">Support Vector Machines (SVM-RBF),</p><p dir="ltr">Random Forests, and</p><p dir="ltr">Principal Component Analysis (PCA) for feature reduction.…"