Using Generative AI for Lunar Image Denoising: Instantaneous Clarity of Ambient eNvironment Capability (ICAN-C)
Using Generative AI for Lunar Image Denoising
Computer Vision↗
Engineering topics
Kelsey Buckles
Publications and source records attributed to Kelsey Buckles.
Machine Learning for Dynamic Test Sensor Placement
There are multiple different algorithms to perform modal test sensor placement optimization: effective independence, residual kinetic energy, iterative Guyan reduction, genetic algorithms, or a brute-force methodology. However, any of these methods may be computationally expensive, especially for structural models with a large number of degrees of freedom. Given the high-cost and the need to optimize the solution, modal sensor placement is a great application for machine learning (ML) algorithms. In this paper, we will apply ML algorithms to determine the optimal sensor locations for simple and complex structures. We will also discuss the benefits and drawbacks of using machine learning over other sensor placement algorithms.
Kelsey Buckles↗