The mAP for all algorithms and 80% of the data used for training. by Mohammad Amin Fraiwan (20469541)

“…<p>The mAP for all algorithms and 80% of the data used for training.</p>…”

The mAP for all algorithms and 50% of the data used for training. by Mohammad Amin Fraiwan (20469541)

“…<p>The mAP for all algorithms and 50% of the data used for training.</p>…”

The mAP for all algorithms and 60% of the data used for training. by Mohammad Amin Fraiwan (20469541)

“…<p>The mAP for all algorithms and 60% of the data used for training.</p>…”

Point cloud data registration using the original ICP algorithm. by Mengyuan Yan (14200322)

“…<p>Point cloud data registration using the original ICP algorithm.…”

Uniform Manifold Approximation and Projection (UMAP)-based sorting enhances detection of low-firing rate neurons and boosts mutual information. by Daniel Suárez-Barrera (22676654)

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Impact of multiunit merging on neural information encoding. by Daniel Suárez-Barrera (22676654)

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Summary of key parameters used in the CSCAP algorithm. by Manxing Shi (22367181)

Features selection using the Boruta algorithm. by Nishat Tasnim Thity (21755858)

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Behavior transition networks generated from the sample data of <i>Neolamprologus multifasciatus</i> from the website (S1 Dataset). by Nicolai Kraus (19949667)

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Parameters of the machine learning algorithms used in the study. by Xiaoyan Yang (259084)

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Data generation algorithm. by Aluwani Ramalata (21262977)

Algorithm for optimizing the model using transformer. by Weiling Liu (1465480)

Data collision free processing unit. by Ayesha Waris (21368446)

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

“…</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. …”

Summary of major algorithms used for signal detection. by Feilong Tan (14886395)

Performance of machine learning algorithms. by Wenxue Liu (6877754)

Data propagation algorithm stages. by Fazia Akhtar (21453122)

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Correlation matrices of handcrafted features before and after feature selection. The figure presents two heatmaps illustrating the correlation among 52 handcrafted features derived... by Quang Dung Dinh (20995766)

Dataset: "A Method for Sensitivity Analysis of Automatic Contouring Algorithms Across Different MRI Contrast Weightings Using SyntheticMR" by Lucas McCullum (16521828)

“…<p dir="ltr">For the paper "A Method for Sensitivity Analysis of Automatic Contouring Algorithms Across Different MRI Contrast Weightings Using Synthetic MR" found at: <a href="https://doi.org/10.1101/2025.01.10.25319895" rel="noreferrer" target="_blank">https://doi.org/10.1101/2025.01.10.25319895</a></p><p dir="ltr">This dataset contains the ground truth segmentations from three expert annotators (v1, v2, v3) for the left parotid, right parotid, left submandibular, and right submandibular gland. …”

The data used in the figures. by Yonghui Zhang (279832)

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