Back to Search
Start Over
Atom cloud detection and segmentation using a deep neural network
- Publication Year :
- 2021
- Publisher :
- IOP Publishing, 2021.
-
Abstract
- Funder: Royal Society; doi: http://dx.doi.org/10.13039/501100000288<br />Funder: Trinity College, University of Cambridge; doi: http://dx.doi.org/10.13039/501100000727<br />Funder: John Fell Fund, University of Oxford; doi: http://dx.doi.org/10.13039/501100004789<br />We use a deep neural network (NN) to detect and place region-of-interest (ROI) boxes around ultracold atom clouds in absorption and fluorescence images—with the ability to identify and bound multiple clouds within a single image. The NN also outputs segmentation masks that identify the size, shape and orientation of each cloud from which we extract the clouds’ Gaussian parameters. This allows 2D Gaussian fits to be reliably seeded thereby enabling fully automatic image processing. The method developed performs significantly better than a more conventional method based on a standardized image analysis library (Scikit-image) both for identifying ROI and extracting Gaussian parameters.
- Subjects :
- Physics
Paper
Artificial neural network
Cloud detection
Atom (order theory)
object detection
Molecular physics
image processing
Human-Computer Interaction
machine learning
deep neural networks
46 Information and Computing Sciences
Artificial Intelligence
instance segmentation
4611 Machine Learning
Segmentation
ultracold quantum matter
4601 Applied Computing
Software
Bayesian optimization
Subjects
Details
- Database :
- OpenAIRE
- Accession number :
- edsair.doi.dedup.....11d15e43a428a1be83558288c68c810f