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Research at Rochester: Rajaoberison helps explore the universe through machine learning - Vimarsana News

Research at Rochester: Rajaoberison helps explore the universe through machine learning

Rajaoberison writes machine learning algorithms to help James Webb’s 18 primary mirrors position themselves and counter piston phase error.

NASA's James Webb Space Telescope captures its first PHOTONS - Vimarsana News

NASA's James Webb Space Telescope captures its first PHOTONS

The infrared observatory launched on Christmas Day last year, taking off from the European Space Agency spaceport in French Guiana, on an Ariane 5 rocket.

"Reconstruction of isolated moving objects by motion-induced phase shif" by Ke Wu, Min Li et al. - Vimarsana News

"Reconstruction of isolated moving objects by motion-induced phase shif" by Ke Wu, Min Li et al.

The reconstruction of moving objects based on phase shifting profilometry has attracted intensive interests. Most of the methods introduce the phase shift by projecting multiple fringe patterns, which is undesirable in moving object reconstruction as the errors caused by the motion will be intensified when the number of the fringe pattern is increased. This paper proposes the reconstruction of the isolated moving object by projecting two fringe patterns with different frequencies. The phase shift required by the phase shifting profilometry is generated by the object motion, and the model descr...

Source: uow.edu.au
"Modeling of Correlated Complex Sea Clutter Using Unsupervised Phase Re" by Liwu Wen, Jinshan Ding et al. - Vimarsana News

"Modeling of Correlated Complex Sea Clutter Using Unsupervised Phase Re" by Liwu Wen, Jinshan Ding et al.

Abstract The spatially and temporally correlated sea clutter with phase information is valuable for marine radar applications. The major difficulty of coherent sea clutter modeling is the generation of the continuous phases. This article presents a new phase retrieval approach for modeling the correlated complex sea clutter based on unsupervised neural networks. The unsupervised short-term and long-term neural networks have been developed for the phase retrieval on different term scales. Both these networks have the same input layer and feature extraction module, and however, the number of ou...

Source: uow.edu.au