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Antennas and Propagation Research From Large-Scale Unstructured Data With Machine Learning: A review and predictions (2023)

First Author: Cha Y

Attributed to: Adaptive Tools for Electromagnetics and Materials Modelling to Bridge the Gap between Design and Manufacturing (AOTOMAT) funded by EPSRC

Abstract

No abstract provided

Bibliographic Information

Digital Object Identifier: http://dx.doi.org/10.1109/map.2023.3290385

Publication URI: http://dx.doi.org/10.1109/map.2023.3290385

Type: Journal Article/Review

Parent Publication: IEEE Antennas and Propagation Magazine

Issue: 5