يعرض 1 - 20 نتائج من 211 نتيجة بحث عن '(( python code presented ) OR ( python after implementation ))', وقت الاستعلام: 0.34s تنقيح النتائج
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    Photoelectron Metrology (LBNL Oct 2024) حسب Paul Hockett (100955)

    منشور في 2024
    الموضوعات:
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    Resolving Harvesting Errors in Institutional Repository Migration : Using Python Scripts with VS Code and LLM Integration. حسب satoshi hashimoto(橋本 郷史) (18851272)

    منشور في 2025
    "…Therefore, we decided to create a dedicated Python program using Large Language Model (LLM)-assisted coding.…"
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    PYTHON حسب Kan Jia (21666161)

    منشور في 2025
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    Real-Time Optical Imaging Acquisition and Processing in Python: A Practical Guide Using CAS: Code Repository حسب Michael Hughes (8821646)

    منشور في 2025
    "…</p><p dir="ltr">This repository contains code to accompany the paper:</p><p><br></p><p dir="ltr">Real-Time Optical Imaging Acquisition and Processing in Python: A Practical Guide Using CAS</p><p><br></p><p dir="ltr">Consult the paper for further details and explanation of what is included in this repository.…"
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    Python sript. حسب Kan Jia (6438599)

    منشور في 2025
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    2D Orthogonal Planes Split: <b>Python</b> and <b>MATLAB</b> code | <b>Source Images</b> for Figures حسب Nektarios Valous (20715650)

    منشور في 2025
    "…<p dir="ltr">Python scripts, Jupyter notebooks, and MATLAB code demonstrate functionalities such as re-colorization, de-colorization, contrast enhancement, re-staining, and stain separation on test images using the 2D orthogonal planes split. …"
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    Supplementary data for PCI-based pavement modelling: code, presentation, and additional analysis حسب Azam Amir (21505033)

    منشور في 2025
    "…<p dir="ltr"><br>This is data for PCI-based pavement modeling: code, presentation, and analysis :</p><p dir="ltr">· A link to the Python code used in the analysis,</p><p dir="ltr">· Presentation slides summarizing key findings, and</p><p dir="ltr">· Analysis results.…"
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    Code interpreter with LLM. حسب Jin Lu (428513)

    منشور في 2025
    "…<div><p>This paper presents a novel approach to enhancing educational question-answering (Q&A) systems by combining Retrieval-Augmented Generation (RAG) with Large Language Model (LLM) Code Interpreters. …"
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