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Found 4 papers, 1 papers with code
EEE, Remediating the failure of machine learning models via a network-based optimization patch
To improve optimization efficiency and convergence, the most important metrics in the context of this research, we follow a three-faceted approach based on the error from the validation process.
Spatially-resolved Thermometry from Line-of-Sight Emission Spectroscopy via Machine Learning
The aim of this research is to explore the use of data-driven models in measuring temperature distributions in a spatially resolved manner using emission spectroscopy data.
Flame-state monitoring based on very low number of visible or infrared images via few-shot learning
We analyzed the training process, test performance and inference speed of two algorithms on both image formats, and also used t-SNE to visualize learned features.
Self-Validated Physics-Embedding Network: A General Framework for Inverse Modelling
Physics-based inverse modeling techniques are typically restricted to particular research fields, whereas popular machine-learning-based ones are too data-dependent to guarantee the physical compatibility of the solution.
