|
26711 |
Toward a general and interpretable umami taste predictor using a multi-objective machine learning approach
Enthalten in Scientific reports Bd. 12, 16.12.2022, Nr. 1, date:12.2022: 1-11
|
|
|
|
26712 |
Toward a generalizable machine learning workflow for neurodegenerative disease staging with focus on neurofibrillary tangles
Enthalten in Acta Neuropathologica Communications Bd. 11, 18.12.2023, Nr. 1, date:12.2023: 1-20
|
|
|
|
26713 |
Toward a globally lunar calendar: a machine learning-driven approach for crescent moon visibility prediction
Enthalten in Journal of Big Data Bd. 11, 12.8.2024, Nr. 1, date:12.2024: 1-23
|
|
|
|
26714 |
Toward a Machine Learning and Software Defined Network Approaches to Manage Miners’ Reputation in Blockchain
Enthalten in Journal of network and systems management Bd. 28, 23.4.2020, Nr. 3, date:7.2020: 478-501
|
|
|
|
26715 |
Toward artificial intelligence and machine learning-enabled frameworks for improved predictions of lifecycle environmental impacts of functional materials and devices
Enthalten in Materials Research Society: MRS communications Bd. 13, 5.10.2023, Nr. 5, date:10.2023: 795-811
|
|
|
|
26716 |
Toward automated microstructure characterization of stainless steels through machine learning-based analysis of replication micrographs
Enthalten in Journal of materials science: materials in engineering Bd. 19, 26.6.2024, Nr. 1, date:12.2024: 1-15
|
|
|
|
26717 |
Toward Complete Structured Information Extraction from Radiology Reports Using Machine Learning
Enthalten in Journal of digital imaging Bd. 32, 19.6.2019, Nr. 4, date:8.2019: 554-564
|
|
|
|
26718 |
Toward finding strong pareto optimal policies in multi-agent reinforcement learning
Enthalten in Machine learning Bd. 114, 6.2.2025, Nr. 3, date:3.2025: 1-20
|
|
|
|
26719 |
Toward fully automated UED operation using two-stage machine learning model
Enthalten in Scientific reports Bd. 12, 10.3.2022, Nr. 1, date:12.2022: 1-12
|
|
|
|
26720 |
Toward particle-resolved accuracy in Euler–Lagrange simulations of multiphase flow using machine learning and pairwise interaction extended point-particle (PIEP) approximation
Enthalten in Theoretical and computational fluid dynamics Bd. 34, 30.6.2020, Nr. 4, date:8.2020: 401-428
|
|
Administration
