Search alternatives:
code optimization » codon optimization (Expand Search), model optimization (Expand Search), dose optimization (Expand Search)
first detection » fire detection (Expand Search), light detection (Expand Search), target detection (Expand Search)
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data first » data fit (Expand Search)
data code » data model (Expand Search), data came (Expand Search)
code optimization » codon optimization (Expand Search), model optimization (Expand Search), dose optimization (Expand Search)
first detection » fire detection (Expand Search), light detection (Expand Search), target detection (Expand Search)
binary data » primary data (Expand Search), dietary data (Expand Search)
data first » data fit (Expand Search)
data code » data model (Expand Search), data came (Expand Search)
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Region-specific variable importance.
Published 2024“…We investigated the use of ensemble species distribution modeling (ESDM) to predict queen snapper distribution along the coast of Puerto Rico. Using occurrence data and terrain attributes derived from bathymetric datasets at different resolutions, we developed species distribution models unique to each sampling region (west, northeast, and southeast Puerto Rico) using seven different algorithms. …”
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Algoritmo de clasificación de expresiones de odio por tipos en español (Algorithm for classifying hate expressions by type in Spanish)
Published 2024“…</li></ul><p dir="ltr"><b>File Structure</b></p><p dir="ltr">The code generates and saves:</p><ul><li>Weights of the trained model (.h5)</li><li>Configured tokenizer</li><li>Training history in CSV</li><li>Requirements file</li></ul><p dir="ltr"><b>Important Notes</b></p><ul><li>The model excludes category 2 during training</li><li>Implements transfer learning from a pre-trained model for binary hate detection</li><li>Includes early stopping callbacks to prevent overfitting</li><li>Uses class weighting to handle category imbalances</li></ul><p dir="ltr">The process of creating this algorithm is explained in the technical report located at: Blanco-Valencia, X., De Gregorio-Vicente, O., Ruiz Iniesta, A., & Said-Hung, E. (2025). …”
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Data Sheet 1_Development of a two-stage depression symptom detection model: application of neural networks to twitter data.docx
Published 2024“…The first stage, with a binary output classifier, can detect tweets with “Depression Symptom” or “No Symptom” categories with an accuracy of 0.91 and F1-score of 0.90. …”
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Data_Sheet_1_DINTD: Detection and Inference of Tandem Duplications From Short Sequencing Reads.docx
Published 2020“…The major principle of the proposed method is that it first extracts read depth and mapping quality signals, then uses the DBSCAN (Density-Based Spatial Clustering of Applications with Noise) algorithm to find the possible TD regions. …”
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Flow diagram of the automatic animal detection and background reconstruction.
Published 2020“…(K) Using the local threshold, each new image is binarized and then subtracted from the first image as shown in panel (J, bottom). If the identical blob that was detected in panel J (bottom) is found in any of the new subtracted binary images (cyan arrow), the animal is considered as having left its original position, and the algorithm continues. …”
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PathOlOgics_RBCs Python Scripts.zip
Published 2023“…<p dir="ltr">The first algorithm for segmentation and localization (see PathOlOgics_script_1; segment & localize using a pen) relied on manually tracing the borders of each cell using a digital pen tool on a big touchscreen display showing source images/patches. …”
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Fortran & C++: design fractal-type optical diffractive element
Published 2022“…</p> <p>(4) export geometry/optics raw data and figures for binary DOE devices.</p> <p><br></p> <p>[Wolfram Mathematica code "square_triangle_DOE.nb"]:</p> <p>read the optimized binary DOE document (after Fortran & C++ code) to calculate its diffractive fields for comparison.…”