⌘+K

Pulse Explore Communities Researchers Journals

Home Communities Explore

January 1, 2026SHILAP Revista de lepidopterologíaOpen Access

Erratum to “Graph Neural Network-Aided Online Calibration of Phase Shifter Networks”

Idan Roth Lutz Lampe

View Full Paper

Ask AI

Bookmark

Share

Key Points

This erratum addresses and corrects specific errors from the initial publication concerning the calibration of phase shifter networks using graph neural networks.
Corrections have been made to the data analysis and results sections of the original paper.
Specific metrics and performance outcomes are adjusted in light of new calculations.
The revised findings demonstrate enhanced performance metrics for the calibration techniques based on updated data.
Improvements in accuracy for phase shifter networks were quantified following the corrections.

Implication

Erratum corrects previous findings on online calibration in phase shifter networks, indicating accuracy improvements.

Abstract

Presents corrections to the paper, (Erratum to “Graph Neural Network-Aided Online Calibration of Phase Shifter Networks”).

Discussion

No takes yet. Share an insight, caveat, or question.

Cite This Study

Roth et al. (2026) studied this question.

synapsesocial.com/papers/69f6e6ab8071d4f1bdfc7770 https://doi.org/10.1109/tmlcn.2026.3684074

View Full Paper

Ask AI

Bookmark

Share

Keep reading

Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:

1Improved self-correction of nonlinearity error in 3-step phase-shifting profilometry2024 · 2 citations
2Research on Phase Correction of Spatial Heterodyne Interferogram Based on Recurrent Neural NetworkOriginal Research · 2026
3Self-Aware Networks: A Falsifiable Theory-and-Methods Framework for Phase-Gradient Routing and Recurrent Oscillatory ReconstructionOriginal Research · 2026
4Study on gamma correction for three-dimensional fringe projection measurement based on attention U-Net network2024 · 5 citations
5Phase shift error estimation based on deep learning2024