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26291 |
Providing and evaluating a comprehensive model for detecting fraudulent electronic payment card transactions with a two-level filter based on flow processing in big data
Enthalten in International journal of information technology Bd. 15, 4.10.2023, Nr. 8, date:12.2023: 4161-4166
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26292 |
Proximity Detection During Epidemics: Direct UWB TOA Versus Machine Learning Based RSSI
Enthalten in International journal of wireless information networks Bd. 29, 14.10.2022, Nr. 4, date:12.2022: 480-490
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26293 |
Pruning during training by network efficacy modeling
Enthalten in Machine learning Bd. 112, 14.3.2023, Nr. 7, date:7.2023: 2653-2684
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26294 |
PSO-based Machine Learning Methods for Predicting Ground Surface Displacement Induced by Shallow Underground Excavation Method
Enthalten in Taehan-t'omok-hakhoe: KSCE journal of civil engineering Bd. 27, 22.9.2023, Nr. 11, date:11.2023: 4948-4961
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26295 |
PT4Rec: a universal prompt-tuning framework for graph contrastive learning-based recommendations
Enthalten in Machine learning Bd. 114, 6.2.2025, Nr. 3, date:3.2025: 1-20
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26296 |
Public subsidies and innovation: a doubly robust machine learning approach leveraging deep neural networks
Enthalten in Empirical economics Bd. 64, 11.5.2023, Nr. 6, date:6.2023: 3121-3165
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26297 |
Publicly available machine learning models for identifying opioid misuse from the clinical notes of hospitalized patients
Enthalten in BMC medical informatics and decision making Bd. 20, 29.4.2020, Nr. 1, date:12.2020: 1-11
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26298 |
Publisher Correction: 2023—A twofold commemoration: the 100th birthday of Walsh functions and the 50th anniversary of Professor Joseph Leonard Walsh’s death
Enthalten in Sampling theory, signal processing, and data analysis Bd. 22, 3.4.2024, Nr. 1, date:6.2024: 1-2
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26299 |
Publisher Correction: A hybrid explainable model based on advanced machine learning and deep learning models for classifying brain tumors using MRI images
Enthalten in Scientific reports Bd. 15, 11.3.2025, Nr. 1, date:12.2025: 1
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26300 |
Publisher Correction: A robust and interpretable ensemble machine learning model for predicting healthcare insurance fraud
Enthalten in Scientific reports Bd. 15, 13.5.2025, Nr. 1, date:12.2025: 1
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