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.
Stay updated with breaking news from Phase Retrieval. Get real-time updates on events, politics, business, and more. Visit us for reliable news and exclusive interviews.
Rajaoberison writes machine learning algorithms to help James Webb’s 18 primary mirrors position themselves and counter piston phase error.
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.
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...
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...