بدائل البحث:
effective implementation » effective prevention (توسيع البحث)
python effective » proven effective (توسيع البحث), 1_the effective (توسيع البحث), 2_the effective (توسيع البحث)
python model » python tool (توسيع البحث), action model (توسيع البحث), motion model (توسيع البحث)
effective implementation » effective prevention (توسيع البحث)
python effective » proven effective (توسيع البحث), 1_the effective (توسيع البحث), 2_the effective (توسيع البحث)
python model » python tool (توسيع البحث), action model (توسيع البحث), motion model (توسيع البحث)
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<b>Code and derived data for</b><b>Training Sample Location Matters: Accuracy Impacts in LULC Classification</b>
منشور في 2025"…</li><li>Python/Kaggle notebooks (<code>.ipynb</code>): reproducibility pipeline for accuracy metrics and statistical analysis.…"
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Simple implementation examples of agent AI on free energy calculation and phase-field simulation
منشور في 2025"…</p> <p>Using Gibbs energy calculations and diffusion simulations as examples, we demonstrated the implementation method and usefulness of simple agent AI, where sample python codes are distributed as supplemental materials.…"
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Performance comparison of cyber security techniques in IoMT healthcare devices.
منشور في 2025الموضوعات: -
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The codes and data for "A Graph Convolutional Neural Network-based Method for Predicting Computational Intensity of Geocomputation"
منشور في 2025"…</li><li>The <b>CIPrediction</b> folder contains model training code.</li><li>The <b>ParallelComputation</b> folder contains geographic computation code.…"
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The codes and data for "A Graph Convolutional Neural Network-based Method for Predicting Computational Intensity of Geocomputation"
منشور في 2025"…</li><li>The <b>CIPrediction</b> folder contains model training code.</li><li>The <b>ParallelComputation</b> folder contains geographic computation code.…"
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120
Data and code for: Automatic fish scale analysis
منشور في 2025"…</p><h3>Includeed in this repository:</h3><ul><li><b>Raw data files:</b></li><li><code>comparison_all_scales.csv</code> – comparison_all_scales.csv - manually verified vs. automated measurements of 1095 coregonid scales</li></ul><ul><li><ul><li><code>Validation_data.csv</code> – manually measured scale data under binocular</li><li><code>Parameter_correction_numeric.csv</code> – calibration data (scale radius vs. fish length/weight)</li></ul></li><li><b>Statistical results:</b></li><li><ul><li><code>comparison_stats_core_variables.csv</code> – verification statistics (bias, relative error, limits of agreement)</li><li><code>Validation_statistics.csv</code> – summary statistics and model fits (manual vs. automated)</li></ul></li><li><b>Executable script (not GUI):</b></li><li><ul><li><code>Algorithm.py</code> – core processing module for scale feature extraction<br>→ <i>Note: The complete Coregon Analyzer application (incl. …"