يعرض 181 - 200 نتائج من 297 نتيجة بحث عن '(( ((python model) OR (python code)) implemented ) OR ( python tool implementing ))', وقت الاستعلام: 0.35s تنقيح النتائج
  1. 181

    Examples of tweets texts (Portuguese). حسب Sylvia Iasulaitis (8301189)

    منشور في 2025
    "…Python algorithms were developed to model each primary collection type. …"
  2. 182

    Methodological flowchart. حسب Sylvia Iasulaitis (8301189)

    منشور في 2025
    "…Python algorithms were developed to model each primary collection type. …"
  3. 183

    Number of tweets collected per query and type. حسب Sylvia Iasulaitis (8301189)

    منشور في 2025
    "…Python algorithms were developed to model each primary collection type. …"
  4. 184

    Examples of tweets texts (English). حسب Sylvia Iasulaitis (8301189)

    منشور في 2025
    "…Python algorithms were developed to model each primary collection type. …"
  5. 185

    Users information. حسب Sylvia Iasulaitis (8301189)

    منشور في 2025
    "…Python algorithms were developed to model each primary collection type. …"
  6. 186

    Data Sheet 1_COCαDA - a fast and scalable algorithm for interatomic contact detection in proteins using Cα distance matrices.pdf حسب Rafael Pereira Lemos (9104911)

    منشور في 2025
    "…Here, we introduce COCαDA (COntact search pruning by Cα Distance Analysis), a Python-based command-line tool for improving search pruning in large-scale interatomic protein contact analysis using alpha-carbon (Cα) distance matrices. …"
  7. 187

    Advancing Solar Magnetic Field Modeling حسب Carlos António (21257432)

    منشور في 2025
    "…<br><br>We developed a significantly faster Python code built upon a functional optimization framework previously proposed and implemented by our team. …"
  8. 188
  9. 189

    Performance Benchmark: SBMLNetwork vs. SBMLDiagrams Auto-layout. حسب Adel Heydarabadipour (22290905)

    منشور في 2025
    "…<p>Log–log plot of median wall-clock time for SBMLNetwork’s C++-based auto-layout engine (blue circles, solid fit) and SBMLDiagrams’ implementation of the pure-Python NetworkX spring_layout algorithm (red squares, dashed fit), applied to synthetic SBML models containing 20–2,000 species, with a fixed 4:1 species-to-reaction ratio. …"
  10. 190

    HCC Evaluation Dataset and Results حسب Jens-Rene Giesen (18461928)

    منشور في 2024
    "…The only requirement for running this script is a Python 3.6+ interpreter as well as an installation of the <code>numpy</code> package. …"
  11. 191

    Overview of deep learning terminology. حسب Aaron E. Maxwell (8840882)

    منشور في 2024
    "…This paper introduces the geodl R package, which supports pixel-level classification applied to a wide range of geospatial or Earth science data that can be represented as multidimensional arrays where each channel or band holds a predictor variable. geodl is built on the torch package, which supports the implementation of DL using the R and C++ languages without the need for installing a Python/PyTorch environment. …"
  12. 192

    Compiled Global Dataset on Digital Business Model Research حسب Dimas Fauzan Aryadefa (22123186)

    منشور في 2025
    "…</p><p dir="ltr">For the modeling component, annual publication growth is projected from 2025–2034 using a logistic growth model (S-curve) implemented in Python. …"
  13. 193

    Hippocampal and cortical activity reflect early hyperexcitability in an Alzheimer's mouse model حسب Marina Diachenko (19739092)

    منشور في 2025
    "…<p dir="ltr">The <i>zip</i> file contains the code for the functional excitation-inhibition ratio (fE/I) and theta-gamma (θ-γ) phase-amplitude coupling (PAC) analyses described in the paper titled "<b>Hippocampal and cortical activity reflect early </b><b>hyperexcitability</b><b> in an Alzheimer's mouse model</b>" submitted to <i>Brain Communications</i> in April 2025.…"
  14. 194

    Iterative Methods for Vecchia-Laplace Approximations for Latent Gaussian Process Models حسب Pascal Kündig (19824557)

    منشور في 2024
    "…In particular, we obtain a speed-up of an order of magnitude compared to Cholesky-based calculations and a 3-fold increase in prediction accuracy in terms of the continuous ranked probability score compared to a state-of-the-art method on a large satellite dataset. All methods are implemented in a free C++ software library with high-level Python and R packages. …"
  15. 195

    Numerical analysis and modeling of water quality indicators in the Ribeirão João Leite reservoir (Goiás, Brazil) حسب Amanda Bueno de Moraes (22559249)

    منشور في 2025
    "…The code implements a statistical–computational workflow for parameter selection (VIF, Bartlett and KMO tests, PCA and FA with <i>varimax</i>) and then trains and evaluates machine-learning models to predict three key physico-chemical indicators: turbidity, true color, and total iron. …"
  16. 196

    Neural-Signal Tokenization and Real-Time Contextual Foundation Modelling for Sovereign-Scale AGI Systems حسب Lakshit Mathur (20894549)

    منشور في 2025
    "…The work advances national AI autonomy, real-time cognitive context modeling, and ethical human-AI integration.</p><p dir="ltr"><b>Availability</b> — The repository includes LaTeX sources, trained model checkpoints, Python/PyTorch code, and synthetic datasets. …"
  17. 197

    face recognation with Flask حسب Muammar, SST, M.Kom (21435692)

    منشور في 2025
    "…</li><li><b>Face Recognition Engine:</b> Compares detected faces to known faces using deep learning models (e.g., <code>face_recognition</code>, based on dlib’s ResNet).…"
  18. 198

    Image 1_Differential diagnosis of pneumoconiosis mass shadows and peripheral lung cancer using CT radiomics and the AdaBoost machine learning model.tif حسب Xiaobing Li (291454)

    منشور في 2025
    "…LR, SVM, and AdaBoost algorithms were implemented using Python to build the models. In the training set, the accuracies of the LR, SVM, and AdaBoost models were 79.4, 84.0, and 80.9%, respectively; the sensitivities were 74.1, 74.1, and 81.0%, respectively; the specificities were 83.6, 91.8, and 80.8%, respectively; and the AUC values were 0.837, 0.886, and 0.900, respectively. …"
  19. 199

    Image 2_Differential diagnosis of pneumoconiosis mass shadows and peripheral lung cancer using CT radiomics and the AdaBoost machine learning model.tif حسب Xiaobing Li (291454)

    منشور في 2025
    "…LR, SVM, and AdaBoost algorithms were implemented using Python to build the models. In the training set, the accuracies of the LR, SVM, and AdaBoost models were 79.4, 84.0, and 80.9%, respectively; the sensitivities were 74.1, 74.1, and 81.0%, respectively; the specificities were 83.6, 91.8, and 80.8%, respectively; and the AUC values were 0.837, 0.886, and 0.900, respectively. …"
  20. 200