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Ergebnis der Suche nach: "Machine Learning"
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13841 - 13850 von 13855
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Artikel 13841 With super SDMs (machine learning, open access big data, and the cloud) towards more holistic global squirrel hotspots and coldspots
Enthalten in Scientific reports Bd. 14, 3.3.2024, Nr. 1, date:12.2024: 1-10
Online Ressource
Artikel 13842 WOOD-LEAF UNSUPERVISED CLASSIFICATION OF SILVER BIRCH TREES FOR BIOMASS ASSESSMENT USING OBLIQUE POINT CLOUDS
Enthalten in The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences Bd. XLVIII-1/W2-2023, 2023: 1795-1802. 8 S.
Online Ressource
Artikel 13843 WorMachine: machine learning-based phenotypic analysis tool for worms
Enthalten in BMC biology Bd. 16, 16.1.2018, Nr. 1, date:12.2018: 1-11
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Artikel 13844 Wrist accelerometry and machine learning sensitively capture disease progression in prodromal Parkinson’s disease
Enthalten in npj Parkinson's Disease Bd. 11, 17.6.2025, Nr. 1, date:12.2025: 1-7
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Artikel 13845 X-Detect: explainable adversarial patch detection for object detectors in retail
Enthalten in Machine learning Bd. 113, 19.6.2024, Nr. 9, date:9.2024: 6273-6292
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Artikel 13846 X-ray based radiomics machine learning models for predicting collapse of early-stage osteonecrosis of femoral head
Enthalten in Scientific reports Bd. 15, 20.4.2025, Nr. 1, date:12.2025: 1-13
Online Ressource
Artikel 13847 X-ray Coronary Angiogram images and SYNTAX score to develop Machine-Learning algorithms for CHD Diagnosis
Enthalten in Scientific data Bd. 12, 21.3.2025, Nr. 1, date:12.2025: 1-8
Online Ressource
Artikel 13848 XAI-based cross-ensemble feature ranking methodology for machine learning models
Enthalten in International journal of information technology Bd. 15, 29.4.2023, Nr. 4, date:4.2023: 1759-1768
Online Ressource
Artikel 13849 XAI-TRIS: non-linear image benchmarks to quantify false positive post-hoc attribution of feature importance
Enthalten in Machine learning Bd. 113, 16.7.2024, Nr. 9, date:9.2024: 6871-6910
Online Ressource
Artikel 13850 XGBoost-based machine learning test improves the accuracy of hemorrhage prediction among geriatric patients with long-term administration of rivaroxaban
Enthalten in BMC geriatrics Bd. 23, 10.7.2023, Nr. 1, date:12.2023: 1-12
Online Ressource


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