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20222026
most citedExposNet: A Deep Learning Framework for EMF Exposure Prediction in Complex Urban Environments

2 citations · 2 across the 1 of their papers we have counts for

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eess.SP2026

B-ExposNet: Bayesian Deep Learning for EMF Exposure Mapping with Uncertainty Quantification

Yukun Liu, Shanshan Wang, Paul Lagouanelle +2

Electromagnetic field exposure in urban environments is highly variable, and conventional exposure maps provide a deterministic estimate, without considering its uncertainty. To ad…

eess.SP2026

UrbanEMF: City-Scale EMF Mapping over a Continuous Urban Area with Real-World Base-Station Deployment

Shuangning Li, Chenxin Luo, Shanshan Wang +3

Electromagnetic Fields (EMF) mapping is essential for wireless propagation modeling and are fundamental to a wide range of applications, including spectrum awareness, network plann…