Comparative Analysis of AI Approaches for Human Estimation via Radio Wave Sensing

This ArXiv paper provides a valuable comparative analysis of different AI methodologies for human estimation using radio wave sensing, contributing to a deeper understanding of the trade-offs involved. The research offers insights into accuracy, spatial generalization, and output granularity, crucial factors for practical applications.

• •The paper evaluates rule-based, machine learning, and deep learning models for human estimation.
• •It examines the performance of these models in terms of accuracy, spatial generalization, and output granularity.
• •The research provides insights into the strengths and weaknesses of each AI approach for this specific application.