Closed-loop feedback registration for consecutive images of moving flexible targets
Author:
Funder
National Science Foundation
Publisher
Springer Science and Business Media LLC
Subject
Artificial Intelligence
Link
https://link.springer.com/content/pdf/10.1007/s10489-022-04068-0.pdf
Reference31 articles.
1. Ma Y, Niu D, Zhang J, Zhao X, Yang B, Zhang C (2022) Unsupervised deformable image registration network for 3D medical images. Appl Intell 52:766–779. https://doi.org/10.1007/s10489-021-02196-7
2. Kawulok M, Benecki P, Piechaczek S, Hrynczenko K, Kostrzewa D, Nalepa J (2019) Deep learning for multiple-image super-resolution. IEEE Geosci Remote Sens Lett 17:1062–1066
3. Devi PRS, Baskaran R (2021) SL2E-AFRE : personalized 3D face reconstruction using autoencoder with simultaneous subspace learning and landmark estimation. Appl Intell 51:2253–2268. https://doi.org/10.1007/s10489-020-02000-y
4. Hosseini MS, Moradi MH (2022) Adaptive fuzzy-SIFT rule-based registration for 3D cardiac motion estimation. Appl Intell 52:1615–1629. https://doi.org/10.1007/s10489-021-02430-2
5. Mehmood Z, Mahmood T, Javid MA (2018) Content-based image retrieval and semantic automatic image annotation based on the weighted average of triangular histograms using support vector machine. Appl Intell 48:166–181. https://doi.org/10.1007/s10489-017-0957-5
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