4 papers
Real-Time Drone Detection in Event Cameras via Per-Pixel Frequency Analysis
Michael Bezick, Majid Sahin
Detecting fast-moving objects, such as unmanned aerial vehicle (UAV), from event camera data is challenging due to the sparse, asynchronous nature of the input. Traditional Discret…
PearSAN: A Machine Learning Method for Inverse Design using Pearson Correlated Surrogate Annealing
Michael Bezick, Blake A. Wilson, Vaishnavi Iyer +6
PearSAN is a machine learning-assisted optimization algorithm applicable to inverse design problems with large design spaces, where traditional optimizers struggle. The algorithm l…
Robust Point Cloud Reinforcement Learning via PCA-Based Canonicalization
Michael Bezick, Vittorio Giammarino, Ahmed H. Qureshi
Reinforcement Learning (RL) from raw visual input has achieved impressive successes in recent years, yet it remains fragile to out-of-distribution variations such as changes in lig…
Machine-Learning-Assisted Photonic Device Development: A Multiscale Approach from Theory to Characterization
Yuheng Chen, Alexander Montes McNeil, Taehyuk Park +16
Photonic device development (PDD) has achieved remarkable success in designing and implementing new devices for controlling light across various wavelengths, scales, and applicatio…