|
42941 |
Using of Machine Learning Capabilities to Predict Double Phosphate Structures for Biomedical Applications
Enthalten in Journal of surface investigation Bd. 18, 15.7.2024, Nr. 3, date:6.2024: 633-640
|
|
|
|
42942 |
USING OPEN DATA CUBE ON THE CLOUD TO INVESTIGATE FOOD SECURITY BY MEANS OF CROPLAND CHANGES IN DJIBOUTI
Enthalten in The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences Bd. XLIII-B3-2022, 2022: 1039-1044. 6 S.
|
|
|
|
42943 |
Using Optimized Deep Learning to Predict Daily Streamflow: A Comparison to Common Machine Learning Algorithms
Enthalten in Water resources management Bd. 36, 17.1.2022, Nr. 2, date:1.2022: 699-716
|
|
|
|
42944 |
Using Passive Multi-Modal Sensor Data for Thermal Simulation of Urban Surfaces
Enthalten in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences Bd. X-2-2024, 2024: 17-24. 8 S.
|
|
|
|
42945 |
Using prognostic signatures and machine learning to identify core features associated with response to CDK4/6 inhibitor-based therapy in metastatic breast cancer
Enthalten in Oncogene Bd. 44, 26.2.2025, Nr. 19, date:5.2025: 1387-1399
|
|
|
|
42946 |
Using published pathway figures in enrichment analysis and machine learning
Enthalten in BMC genomics Bd. 24, 25.11.2023, Nr. 1, date:12.2023: 1-13
|
|
|
|
42947 |
Using quantum atomics and machine learning to advance picotechnology
Enthalten in Theoretical chemistry accounts Bd. 143, 26.9.2024, Nr. 10, date:10.2024: 1-9
|
|
|
|
42948 |
Using remote sensing data for geological mapping in semi-arid environment: a machine learning approach
Enthalten in Earth science informatics Bd. 15, 3.2.2022, Nr. 1, date:3.2022: 485-496
|
|
|
|
42949 |
Using remote sensing, process-based crop models, and machine learning to evaluate crop rotations across 20 million hectares in Western Australia
Enthalten in Agronomy for sustainable development Bd. 42, 12.12.2022, Nr. 6, date:12.2022: 1-14
|
|
|
|
42950 |
Using sentinel-2 satellite images and machine learning algorithms to predict tropical pasture forage mass, crude protein, and fiber content
Enthalten in Scientific reports Bd. 14, 15.4.2024, Nr. 1, date:12.2024: 1-14
|
|
Administration
