Gene pairs of the epistastic interactions detected on the seven GWAS data using Epi-SSA. by Liyan Sun (760586)

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Part of genes of the epistastic interactions detected on the seven GWAS data using Epi-SSA. by Liyan Sun (760586)

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Posterior predicted sensitivity, specificity, PPV, NPV for each algorithm combination under the ‘AND’ rule and ‘OR’ rule in Model-3 in the primary analysis. by Jia Wei (120974)

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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)

Part of gene pairs of the epistastic interactions detected on the seven GWAS data using Epi-SSA. by Liyan Sun (760586)

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Scripts for GC, CRC, and IBD in Python and R by Animesh Acharjee (6400427)

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

“…<p dir="ltr">This dataset accompanies the publication:<br><b>"Automatic fish scale analysis: age determination, annuli and circuli detection, length and weight back-calculation of coregonid scales"</b><br></p><p dir="ltr">It provides all essential data and statistical outputs used for the <b>verification and validation</b> of the <i>Coregon Analyzer</i> – a Python-based algorithm for automated biometric fish scale measurement.…”

Posterior predicted sensitivity, specificity, PPV, NPV for each algorithm combination under the ‘AND’ rule (a) and ‘OR’ rule (b) in Model-3 in the primary analysis. by Jia Wei (120974)

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Parameter values of the compared algorithms. by Huimin Lu (4434682)

“…Finally, we proposed an escape Coati Optimization Algorithm (eCOA) for global optimization to enhance classification performance. …”

EFGs: A Complete and Accurate Implementation of Ertl’s Functional Group Detection Algorithm in RDKit by Gonzalo Colmenarejo (650249)

Ground-truth annotations and detection results visualization of representative images from the SeaDronesSee dataset captured at different altitudes. by Beigeng Zhao (21637197)

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Structure of the Dynamic Downsampling module. by Xun Li (182737)

“…These results demonstrate the effectiveness of TLINet in addressing the complexities of insulator defect detection in power transmission lines. The code is available at <a href="https://github.com/mazilishang/TLINet" target="_blank">https://github.com/mazilishang/TLINet</a>.…”

UAV aerial image samples of insulator. by Xun Li (182737)

“…These results demonstrate the effectiveness of TLINet in addressing the complexities of insulator defect detection in power transmission lines. The code is available at <a href="https://github.com/mazilishang/TLINet" target="_blank">https://github.com/mazilishang/TLINet</a>.…”

General framework of the proposed TLINet. by Xun Li (182737)

“…These results demonstrate the effectiveness of TLINet in addressing the complexities of insulator defect detection in power transmission lines. The code is available at <a href="https://github.com/mazilishang/TLINet" target="_blank">https://github.com/mazilishang/TLINet</a>.…”

Initialization Parameters Of Our Method. by Xun Li (182737)

“…These results demonstrate the effectiveness of TLINet in addressing the complexities of insulator defect detection in power transmission lines. The code is available at <a href="https://github.com/mazilishang/TLINet" target="_blank">https://github.com/mazilishang/TLINet</a>.…”

Details of the five public datasets. by Xun Li (182737)

“…These results demonstrate the effectiveness of TLINet in addressing the complexities of insulator defect detection in power transmission lines. The code is available at <a href="https://github.com/mazilishang/TLINet" target="_blank">https://github.com/mazilishang/TLINet</a>.…”

The source code includes training/validation scripts, pre-trained model weights, configuration files, and data processing tools. by Ju Liang (4277062)

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

Global Aridity Index and Potential Evapotranspiration Climate Database v3.1 - Algorithm Code (Python) by Robert Zomer (12796235)

Performance of algorithms outside the training species. by Sven B. Gould (12237287)