# Machine-Learning Classification of Closed and Open Radiating Wires from Near Magnetic or Electric Field Scan Images

arXiv: https://arxiv.org/abs/2104.09277 · HTML: https://mlsanity.com/paper/2104.09277/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 0 of its 4 references that are in the map.
- First posted on arXiv 16 Mar 2021.

## Abstract (arXiv)

Sets of intelligent classifiers are applied to the near-field scan-data in order to automatically classify the shape of radiating wirings. The support vector machine, k-nearest neighbors algorithm, and Gaussian process classifications are trained using the near-field radiation pattern of diverse radiating wire configurations. Leave-one-out cross-validation is used for estimating the performance of the predictive models. The output of this research is a software package well-suited to be retrained based on any measured near-field databank to automate the identification of magnetic-type or electric-type of the radiating coupling sources.
