بدائل البحث:
python model » python tool (توسيع البحث), action model (توسيع البحث), motion model (توسيع البحث)
consider » considered (توسيع البحث)
python model » python tool (توسيع البحث), action model (توسيع البحث), motion model (توسيع البحث)
consider » considered (توسيع البحث)
-
121
<b>AI for imaging plant stress in invasive species </b>(dataset from the article https://doi.org/10.1093/aob/mcaf043)
منشور في 2025"…In total, 75 % of the labelled observations were assigned to train and 25 % to test the model. To evaluate the model performance, the root mean squared root error (RMSE, the standard deviation of the residuals that represents the mean difference between the prediction and the real value for the test set) and <i>R</i><sup>2</sup> were used, which was calculated using r2_score() from <i>Scikit-learn</i> metrics. …"
-
122
-
123
Overview of deep learning terminology.
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. …"
-
124
Moulin distributions during 2016-2021 on the southwest Greenland Ice Sheet
منشور في 2025"…</p><p><br></p><ul><li>00_Satellite-derived moulins: Moulins directly mapped from Sentinel-2 imagery, representing actual moulin positions;</li><li>01_Snapped moulins: Moulins snapped to DEM-modeled supraglacial drainage networks, primarily used for analyses;</li><li>02_Moulin recurrences: Recurring moulins determined from the snapped moulins;</li><li>03_Internally drained catchments: Internally drained catchment (IDC) associated with each moulin;</li><li>04_Surface meltwater runoff: surface meltwater runoff calculated from MAR for the study area, elevation bins, and IDCs; </li><li>05_DEM-derived: Topographic features modeled from ArcticDEM, including elevation bins, depressions and drainage networks;</li><li>06_GWR: Variables for conducting geographically weighted regression (GWR) analysis;</li></ul><p><br></p><ul><li>Code_01_Mapping moulins on the southwestern GrIS.ipynb: A Jupyter Notebook to analyze moulin distributions, reproducing most of the analyses and figures presented in the manuscript using the provided datasets;</li><li>Code_02_pre1_calculate Strain Rate from XY ice velocity.py: A preprocessing Python script to calculate strain rate for the GWR analysis;</li><li>Code_02_pre2_calculate Driving Stress from ice thickness and surface slope.py: A preprocessing Python script to calculate driving stress for the GWR analysis;</li><li>Code_02_GWR analysis.ipynb: A Jupyter Notebook to conduct the GWR analysis using the provided datasets.…"
-
125
<b>Rethinking neighbourhood boundaries for urban planning: A data-driven framework for perception-based delineation</b>
منشور في 2025"…</p><p dir="ltr"><b>Input:</b></p><ul><li><code>svi_module/svi_data/svi_info.csv</code> - Image metadata from Step 1</li><li><code>perception_module/trained_models/</code> - Pre-trained models</li></ul><p dir="ltr"><b>Command:</b></p><pre><pre>python -m perception_module.pred \<br> --model-weights .…"
-
126
Missing and Unaccounted-for People in Mexico (1960s–2025)
منشور في 2025"…</li><li><b>Requirements File:</b> A <code>requirements.txt</code> file listing the necessary Python libraries to run the script seamlessly.…"
-
127
Supplementary material for "Euler inversion: Locating sources of potential-field data through inversion of Euler's homogeneity equation"
منشور في 2025"…</p><h2>License</h2><p dir="ltr">All Python source code (including <code>.py</code> and <code>.ipynb</code> files) is made available under the MIT license. …"
-
128
Audio Datasets of belt conveyor rollers in mines
منشور في 2024"…</li><li><b>Python Code: </b>This code validates the accuracy and usability of the audio feature datasets in real-time monitoring of belt conveyor roller operational states.…"
-
129
Improving the calibration of an integrated CA-What If? digital planning framework
منشور في 2025"…</p><p dir="ltr">This dataset includes (1) all required data for reproducing the materials within the manuscript, (2) detailed Python codes of the proposed CA-What If? model, and (3) a step-by-step instruction document.…"
-
130
Attention and Cognitive Workload
منشور في 2025"…</p><p dir="ltr">The data for subject 2 do not include the 2nd part of the acquisition (python task) because the equipment stopped acquiring; subject 3 has the 1st (N-Back task and mental subtraction) and the 2nd part (python tutorial) together in the <code>First part</code> folder (file <code>D1_S3_PB_description.json</code> indicates the start and end of each task); subject 4 only has the mental subtraction task in the 1st part acquisition and in subject 8, the subtraction task data is included in the 2nd part acquisition, along with python task.…"
-
131
Social media images of China's terraces
منشور في 2025"…</p><p dir="ltr">These images can be used for training classification models. All code used for model training and testing is available at: https://github.com/chen7092/Deep-learning-for-cultural-ecosystem-services-of-terraces.…"
-
132
Bacterial persistence modulates the speed, magnitude and onset of antibiotic resistance evolution
منشور في 2025"…</p><p dir="ltr">Repository structure</p><p dir="ltr">Fig_1/</p><ul><li>Probability of emergence analysis</li><li>Fig_1.py: contour plot generation</li></ul><p dir="ltr">Fig_2/</p><ul><li>MIC evolution simulations</li><li>Fig_2_a/: R-based simulation analysis</li><li>Fig_2_b/: Python visualization</li><li>Fig_2_c/: speed of resistance evolution analysis</li><li>Fig_2_d/: time to resistance analysis</li></ul><p dir="ltr">Fig_3/</p><ul><li>Distribution analysis</li><li>Fig_3_a-b.R: density plots and bar charts (empirical and simulated)</li></ul><p dir="ltr">Fig_4/</p><ul><li>Mutation analysis</li><li>Fig_4_a-b/: mutation counting analysis</li><li><ul><li>Fig_4_a/: simulation data (sim)</li><li>Fig_4_b/: empirical data (emp)</li></ul></li><li>Fig_4_c/: gene ontology and functional analysis</li></ul><p dir="ltr">Fig_5/</p><ul><li>Large-scale evolutionary simulations</li><li>Fig_5_a-b/: heatmap visualizations</li><li>Fig_5_c/: MIC and extinction analysis (empirical)</li></ul><p dir="ltr">Fig_6/</p><ul><li>Population size effects</li><li>Fig_6.py: population size analysis simulations</li></ul><p dir="ltr">S1_figure/</p><ul><li>Supplementary experimental data</li></ul><p dir="ltr">S2_figure/</p><ul><li>Supplementary frequency analysis</li></ul><p dir="ltr">S3_figure/</p><ul><li>Supplementary probability analysis</li></ul><p dir="ltr">scripts_simulations_cluster/</p><ul><li>Large-scale, cluster-optimized simulations</li></ul><p dir="ltr">complete_data/</p><ul><li>Reference to the full data sheet (full data set deposited elsewhere)</li></ul><p dir="ltr">Script types and languages</p><p dir="ltr">Python scripts (.py)</p><ul><li>Mathematical modeling: survival functions, probability calculations</li><li>Stochastic simulations: tau-leaping population dynamics</li><li>Data processing: mutation analysis, frequency calculations</li><li>Visualization: plotting with matplotlib and seaborn</li><li>Typical dependencies: numpy, pandas, matplotlib, seaborn, scipy</li></ul><p dir="ltr">R scripts (.R)</p><ul><li>Statistical analysis: distribution fitting, density plots</li><li>Advanced visualization: publication-quality figures (ggplot2)</li><li>Data manipulation: dplyr / tidyr workflows</li><li>Typical dependencies: dplyr, tidyr, ggplot2, readxl, cowplot</li></ul><p dir="ltr">Data requirements</p><p dir="ltr">The scripts are designed to run using the complete_data.xlsx file and, where relevant, the raw simulation outputs and empirical data sets as described above. …"
-
133
Satellite monitoring of Greenland wintertime buried lake drainage
منشور في 2025"…Buried_lake_drainage_code</p><p dir="ltr">This folder contains two Python Jupyter Notebooks for detecting wintertime buried lake drainages (BLDs). …"
-
134
2024 HUD Point in Time Count Data by State and CoC with Serious Mental Illness and Chronic Substance Use Counts
منشور في 2025"…</p><p dir="ltr">HUD PIT Count reports for states, Washington, DC, and the 384 CoCs were systematically downloaded from the HUD Exchange website using a Python script developed using Cursor software. Cursor uses large language models, especially Claude Sonnet 4 (Anthropic), to generate code. …"
-
135
Digital Twin for Chemical Sciences
منشور في 2025"…The procedure for generating data in Figure 3 can be found in the demo notebook in Supplementary Code. The procedure for generating data of Figure 4 has been uploaded in fig4_figshare.zip file. …"
-
136
Sonification of Warming Stripes
منشور في 2025"…The sonification was produced using the STRAUSS sonification Python package.</p><p dir="ltr">Here we release:<br>1. …"
-
137
(A) Sampling locations and ranges of <i>I. feisthamelii</i> (purple) and <i>I. podalirius</i> (teal) butterflies.
منشور في 2025"…(B) Sampling locations of butterflies from the <i>Iphiclides</i> HZ. The dashed line represents the approximate HZ center, based on samples collected by Lafranchis et al. …"
-
138
Sonification of Growing Black Hole
منشور في 2024"…We used the open source Python package STRAUSS to produce the sonification (Trayford and Harrison 2023). …"
-
139
Tracking when the number of individuals in the video frame changes.
منشور في 2025"…The removal of unnecessary keypoint data is achieved through a Python code that allows specified ranges of tracking data obtained from DeepLabCut to be rewritten as NaN (no data) (<a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.3003002#pbio.3003002.s019" target="_blank">S1 Protocol</a> and <a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.3003002#pbio.3003002.s010" target="_blank">S10C Fig</a>). …"
-
140
Cognitive Fatigue
منشور في 2025"…<br></p><p dir="ltr"><b>HCI features</b> encompass keyboard, mouse, and screenshot data. Below is a Python code snippet for extracting screenshot files from the screenshots CSV file.…"