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1361 |
Synergetic use of geospatial and machine learning techniques in modelling landslide susceptibility in parts of Shimla to Kinnaur National Highway, Himachal Pradesh
Enthalten in Modeling earth systems and environment Bd. 10, 18.4.2024, Nr. 3, date:6.2024: 4163-4183
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1362 |
Synergistic integration of Multi-View Brain Networks and advanced machine learning techniques for auditory disorders diagnostics
Enthalten in Brain Informatics Bd. 11, 14.1.2024, Nr. 1, date:12.2024: 1-13
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1363 |
Synergizing multiple machine learning techniques and remote sensing for advanced landslide susceptibility assessment: a case study in the Three Gorges Reservoir Area
Enthalten in Environmental earth sciences Bd. 83, 2.4.2024, Nr. 8, date:4.2024: 1-20
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1364 |
Synergizing quantum techniques with machine learning for advancing drug discovery challenge
Enthalten in Scientific reports Bd. 14, 28.12.2024, Nr. 1, date:12.2024: 1-12
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1365 |
Temporal remote sensing based soil salinity mapping in Indo-Gangetic plain employing machine-learning techniques
Enthalten in Indian National Science Academy: Proceedings of the Indian National Science Academy Bd. 89, 20.3.2023, Nr. 2, date:6.2023: 290-305
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1366 |
Texture feature analysis of MRI-ADC images to differentiate glioma grades using machine learning techniques
Enthalten in Scientific reports Bd. 13, 22.9.2023, Nr. 1, date:12.2023: 1-15
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1367 |
The application of machine learning techniques in posttraumatic stress disorder: a systematic review and meta-analysis
Enthalten in npj digital medicine Bd. 7, 9.5.2024, Nr. 1, date:12.2024: 1-13
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1368 |
The atmospheric boundary layer: a review of current challenges and a new generation of machine learning techniques
Enthalten in Artificial intelligence review Bd. 57, 17.10.2024, Nr. 12, date:12.2024: 1-51
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1369 |
The effect of resampling techniques on the performances of machine learning clinical risk prediction models in the setting of severe class imbalance: development and internal validation in a retrospective cohort
Enthalten in Discover artificial intelligence Bd. 4, 26.11.2024, Nr. 1, date:12.2024: 1-17
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1370 |
The effectiveness of data pre-processing methods on the performance of machine learning techniques using RF, SVR, Cubist and SGB: a study on undrained shear strength prediction
Enthalten in Stochastic environmental research and risk assessment Bd. 38, 13.6.2024, Nr. 8, date:8.2024: 3273-3290
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