Mobile Phone Emissions in 5G FR1: Using Statistic Inferences and Deep Learning for Empiric Features Extraction
Author:
Affiliation:
1. IT & Cyber Defense “Nicolae Balcescu” Land Forces Academy,Dept. Communications,Sibiu,Romania
2. Doctoral School of Electrical Engineering, Technical University of Cluj-Napoca,Cluj,Romania
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx8/10615257/10615262/10615263.pdf?arnumber=10615263
Reference22 articles.
1. Three Quarters of a Century of Research on RF Exposure Assessment and Dosimetry—What Have We Learned?
2. Problems in evaluating the health impacts of radio frequency radiation
3. 5G New Radio Requires the Best Possible Risk Assessment Studies: Perspective and Recommended Guidelines
4. NextGEM: Next-Generation Integrated Sensing and Analytical System for Monitoring and Assessing Radiofrequency Electromagnetic Field Exposure and Health
5. Dominance of Smartphone Exposure in 5G Mobile Networks
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