4 citations · 4 across the 2 of their papers we have counts for
2 papers
cs.CV2025
Predicting Performance of Object Detection Models in Electron Microscopy Using Random Forests
Ni Li, Ryan Jacobs, Matthew Lynch +3
Quantifying prediction uncertainty when applying object detection models to new, unlabeled datasets is critical in applied machine learning. This study introduces an approach to es…
cs.CV2024★ 4 cited
Accelerating Domain-Aware Electron Microscopy Analysis Using Deep Learning Models with Synthetic Data and Image-Wide Confidence Scoring
Matthew J. Lynch, Ryan Jacobs, Gabriella Bruno +3
The integration of machine learning (ML) models enhances the efficiency, affordability, and reliability of feature detection in microscopy, yet their development and applicability…