JACoW is a publisher in Geneva, Switzerland that publishes the proceedings of accelerator conferences held around the world by an international collaboration of editors.
@inproceedings{pogorelov:icalepcs2023-tupdp114,
author = {I.V. Pogorelov and S. Calder and J.P. Edelen and R.D. Gregory and G.S. Guyotte and M.J. Henderson and C.M. Hoffmann and M.C. Kilpatrick and B.K. Krishna and B. Vacaliuc},
% author = {I.V. Pogorelov and S. Calder and J.P. Edelen and R.D. Gregory and G.S. Guyotte and M.J. Henderson and others},
% author = {I.V. Pogorelov and others},
title = {{Machine Learning Based Noise Reduction of Neutron Camera Images at ORNL}},
% booktitle = {Proc. ICALEPCS'23},
booktitle = {Proc. 19th Int. Conf. Accel. Large Exp. Phys. Control Syst. (ICALEPCS'23)},
eventdate = {2023-10-09/2023-10-13},
pages = {841--845},
paper = {TUPDP114},
language = {english},
keywords = {neutron, network, timing, target, operation},
venue = {Cape Town, South Africa},
series = {International Conference on Accelerator and Large Experimental Physics Control Systems},
number = {19},
publisher = {JACoW Publishing, Geneva, Switzerland},
month = {02},
year = {2024},
issn = {2226-0358},
isbn = {978-3-95450-238-7},
doi = {10.18429/JACoW-ICALEPCS2023-TUPDP114},
url = {https://jacow.org/icalepcs2023/papers/tupdp114.pdf},
abstract = {{Neutron cameras are utilized at the HB2A powder diffractometer to image the sample for alignment in the beam. Typically, neutron cameras are quite noisy as they are constantly being irradiated. Removal of this noise is challenging due to the irregular nature of the pixel intensity fluctuations and the tendency for it to change over time. RadiaSoft has developed a novel noise reduction method for neutron cameras that inscribes a lower envelope of the image signal. This process is then sped up using machine learning. Here we report on the results of our noise reduction method and describe our machine learning approach for speeding up the algorithm for use during operations. }},
}