Noise Reduction in Flash X-ray Imaging Using Deep Learning

Noise Reduction in Flash X-ray Imaging Using Deep Learning

Recent improvements in deep learning architectures, combined with the strength of modern computing hardware such as graphics processing units, has lead to significant results in the field of image analysis. In this thesis work, locally connected architectures are employed to reduce noise in flash X-...

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Bibliographic Details
Main Author: Sundman, Tobias
Format: Others
Language:English
Published: Uppsala universitet, Avdelningen för beräkningsvetenskap 2018
Subjects:
flash x-ray imaging
machine learning
deep learning
neural network
locally connected layer
autoencoder
LCLS
GPU
tensorflow
python
U-Net
free electron laser
selu
scaled exponential linear unit
diffraction
simulation
residual
concatenation
Engineering and Technology
Teknik och teknologier
Online Access:http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-355731

Internet

http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-355731

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