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processing algorithm » modeling algorithm (Expand Search), routing algorithm (Expand Search), tracking algorithm (Expand Search)
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data code » data model (Expand Search), data came (Expand Search)
processing algorithm » modeling algorithm (Expand Search), routing algorithm (Expand Search), tracking algorithm (Expand Search)
network algorithm » new algorithm (Expand Search)
code algorithm » cosine algorithm (Expand Search), novel algorithm (Expand Search), modbo algorithm (Expand Search)
data code » data model (Expand Search), data came (Expand Search)
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Data and code for: Automatic fish scale analysis
Published 2025“…</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. …”
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TreeMap 2016 Stand Size Code Algorithm (Image Service)
Published 2024“…format=iso19139 "> ISO-19139 metadata</a></li><li> <a href="https://data-usfs.hub.arcgis.com/datasets/usfs::treemap-2016-stand-size-code-algorithm-image-service "> ArcGIS Hub Dataset</a></li><li> <a href="https://apps.fs.usda.gov/fsgisx01/rest/services/RDW_ForestEcology/TreeMap_2016_StandSizeCode_Algorithm/ImageServer "> ArcGIS GeoService</a></li></ul><div> For complete information, please visit <a href="https://data.gov">https://data.gov</a>.…”
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<b>A study on an efficient citrus Huanglong disease detection algorithm based on three-channel aggregated attention</b>
Published 2024“…Additionally, the inference speed increased by 14.6%, fully meeting the real-time requirements for detecting diseases in citrus fields and illustrating the effectiveness and advanced nature of the improved algorithm, thereby providing robust support for the rapid identification of diseases in the citrus cultivation process.…”
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QQESPM-GS - Codes and Data
Published 2025“…<p dir="ltr">Codes and Data for the algorithms, methods and experiments presented in the paper titled "QQESPM-GS: an Efficient Solution for Geo-textual Search Parameterized by Graph-based Spatial Patterns".…”
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