JACoW is a publisher in Geneva, Switzerland that publishes the proceedings of accelerator conferences held around the world by an international collaboration of editors.
TY - CONF AU - Pogorelov, I.V. AU - Calder, S. AU - Edelen, J.P. AU - Gregory, R.D. AU - Guyotte, G.S. AU - Henderson, M.J. AU - Hoffmann, C.M. AU - Kilpatrick, M.C. AU - Krishna, B.K. AU - Vacaliuc, B. ED - Schaa, Volker RW ED - Götz, Andy ED - Venter, Johan ED - White, Karen ED - Robichon, Marie ED - Rowland, Vivienne TI - Machine Learning Based Noise Reduction of Neutron Camera Images at ORNL J2 - Proc. of ICALEPCS2023, Cape Town, South Africa, 09-13 October 2023 CY - Cape Town, South Africa T2 - International Conference on Accelerator and Large Experimental Physics Control Systems T3 - 19 LA - english AB - 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. PB - JACoW Publishing CP - Geneva, Switzerland SP - 841 EP - 845 KW - neutron KW - network KW - timing KW - target KW - operation DA - 2024/02 PY - 2024 SN - 2226-0358 SN - 978-3-95450-238-7 DO - doi:10.18429/JACoW-ICALEPCS2023-TUPDP114 UR - https://jacow.org/icalepcs2023/papers/tupdp114.pdf ER -