Showing 121 - 140 results of 143 for search '(( ((python time) OR (python files)) implementation ) OR ( python proof implementation ))', query time: 0.59s Refine Results
  1. 121

    <b>Use case codes of the DDS3 and DDS4 datasets for bacillus segmentation and tuberculosis diagnosis, respectively</b> by Marly G F Costa (19812192)

    Published 2025
    “…The encoder was implemented with depth-wise separable convolution layers13.…”
  2. 122

    Data and code for: Automatic fish scale analysis by Christian Vogelmann (21646472)

    Published 2025
    “…</i></li></ul></li><li><b>README.txt</b> – detailed file explanations and usage instructions</li></ul><p dir="ltr">The full statistical analysis and visualization pipeline is implemented in R and hosted on GitHub:<br>https://github.com/Birdy332/Automatic-fish-scale-analysis-r-scripts</p><p dir="ltr"><br></p><p dir="ltr">All figures shown in the manuscript can be reproduced using these scripts and the datasets provided here.…”
  3. 123

    kececilayout by Mehmet Keçeci (14301782)

    Published 2025
    “…<p dir="ltr"><b>Kececi Layout (Keçeci Yerleşimi)</b>: A deterministic graph layout algorithm designed for visualizing linear or sequential structures with a characteristic "zig-zag" or "serpentine" pattern.</p><p dir="ltr"><i>Python implementation of the Keçeci layout algorithm for graph visualization.…”
  4. 124

    <b>Code and derived data for</b><b>Training Sample Location Matters: Accuracy Impacts in LULC Classification</b> by Pajtim Zariqi (22155799)

    Published 2025
    “…<p dir="ltr">This repository contains the analysis code and derived outputs for the study <i>“Training Sample Location Matters: Accuracy Impacts in LULC Classification”</i>. The workflow was implemented in Google Earth Engine (JavaScript API) and replicated in Python notebooks (Jupyter/Kaggle) for reproducibility.…”
  5. 125

    Testing Code for JcvPCA and JsvCRP. by Océane Dubois (21989812)

    Published 2025
    “…<p>This file contains the code that implements both metrics in python and apply them on a simulated dataset.…”
  6. 126

    MSc Personalised Medicine at Ulster University by Steven Watterson (100045)

    Published 2025
    “…</p><p dir="ltr">MSc Personalised Medicine is a Master’s programme that can be taken in 1 year full-time or across 2 years part-time. Both full-time and part-time programmes have two intakes and can be started in September or January.…”
  7. 127

    Core-Based Smart Sampling Framework: A Theoretical and Experimental Study on Randomized Partitioning for SAT Problems by DURGHAM QARALLEH (21904172)

    Published 2025
    “…We provide theoretical guarantees on complexity reduction and probabilistic completeness, apply the method to SAT instances, and evaluate its performance using experimental Python implementations. The results show that smart sampling drastically reduces the effective complexity of SAT problems and offers new insights into the structure of NP-complete problems.…”
  8. 128

    Void-Center Galaxies and the Gravity of Probability Framework: Pre-DESI Consistency with VGS 12 and NGC 6789 by Jordan Waters (21620558)

    Published 2025
    “…<br><br><br><b>ORCID ID: https://orcid.org/0009-0009-0793-8089</b><br></p><p dir="ltr"><b>Code Availability:</b></p><p dir="ltr"><b>All Python tools used for GoP simulations and predictions are available at:</b></p><p dir="ltr"><b>https://github.com/Jwaters290/GoP-Probabilistic-Curvature</b><br><br>The Gravity of Probability framework is implemented in this public Python codebase that reproduces all published GoP predictions from preexisting DESI data, using a single fixed set of global parameters. …”
  9. 129
  10. 130

    Supplementary Data: Biodiversity and Energy System Planning - Queensland 2025 by Andrew Rogers (17623239)

    Published 2025
    “…</p><h2>Software and Spatial Resolution</h2><p dir="ltr">The VRE siting model is implemented using Python and relies heavily on ArcGIS for comprehensive spatial data handling and analysis.…”
  11. 131

    Optimized Bayesian regularization-back propagation neural network using data-driven intrusion detection system in Internet of Things by Ashok Kumar K (21441108)

    Published 2025
    “…The proposed DIDS-BRBPNN-BBWOA-IoT method is implemented using Python. The performance of the DIDS-BRBPNN-BBWOA-IoT approach is examined using performance metrics like accuracy, precision, recall, f1-score, specificity, error rate; computation time, and ROC. …”
  12. 132

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

    Published 2025
    “…</p><p dir="ltr">All data are available upon request. The standalone Python implementation of the fE/I algorithm is available under a CC-BY-NC-SA license at <a href="https://github.com/arthur-ervin/crosci" target="_blank">https://github.com/arthur-ervin/crosci</a>. …”
  13. 133

    The codes and data for "A Graph Convolutional Neural Network-based Method for Predicting Computational Intensity of Geocomputation" by FirstName LastName (20554465)

    Published 2025
    “…<h2>A Graph Convolutional Neural Network-based Method for Predicting Computational Intensity of Geocomputation</h2><p><br></p><p dir="ltr">This is the implementation for the paper "A Graph Convolutional Neural Network-based Method for Predicting Computational Intensity of Geocomputation".…”
  14. 134

    The codes and data for "A Graph Convolutional Neural Network-based Method for Predicting Computational Intensity of Geocomputation" by FirstName LastName (20554465)

    Published 2025
    “…<h2>A Graph Convolutional Neural Network-based Method for Predicting Computational Intensity of Geocomputation</h2><p><br></p><p dir="ltr">This is the implementation for the paper "A Graph Convolutional Neural Network-based Method for Predicting Computational Intensity of Geocomputation".…”
  15. 135

    Microscopic Detection and Quantification of Microplastic Particles in Environmental Water Samples by Derek Lam (11944213)

    Published 2025
    “…Image processing algorithms, implemented in Python using adaptive thresholding techniques, were applied to segment particles from the background. …”
  16. 136

    Mean Annual Habitat Quality and Its Driving Variables in China (1990–2018) by ChenXi Zhu (21374876)

    Published 2025
    “…</p><p dir="ltr">(HQ: Habitat Quality; CZ: Climate Zone; FFI: Forest Fragmentation Index; GPP: Gross Primary Productivity; Light: Nighttime Lights; PRE: Mean Annual Precipitation Sum; ASP: Aspect; RAD: Solar Radiation; SLOPE: Slope; TEMP: Mean Annual Temperature; SM: Soil Moisture)</p><p dir="ltr"><br>A Python script used for modeling habitat quality, including mean encoding of the categorical variable climate zone (CZ), multicollinearity testing using Variance Inflation Factor (VIF), and implementation of four machine learning models to predict habitat quality.…”
  17. 137

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

    Published 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. Outputs include both CSV tables and PNG charts that depict historical trends and forward-looking projections. …”
  18. 138

    Landscape Change Monitoring System (LCMS) Conterminous United States Cause of Change (Image Service) by U.S. Forest Service (17476914)

    Published 2025
    “…Detecting trends in forest disturbance and recovery using yearly Landsat time series: 2. TimeSync - Tools for calibration and validation. …”
  19. 139

    Data&Codes.zip by Zer0 Star (20545655)

    Published 2025
    “…</p><p dir="ltr">To facilitate the widespread use of the proposed framework, we have implemented it as the <b><i>ESLocalIndi</i></b> open-source package in Python, making it easily accessible to geographers. …”
  20. 140

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

    Published 2025
    “…COCαDA demonstrated superior performance compared to the other methods, achieving on average 6x faster computation times than advanced data structures like k-d trees from NS, in addition to being simpler to implement and fully customizable. …”