Publications
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Can ML Enhance the Accuracy of Crop Quality Assessment With Radio Frequency Reflectometry?
This article presents a novel approach that integrates AI/ML algorithms-linear regression, random forest, and principal component analysis (PCA) to enhance
Enhancing RF Reflectometry for Crop Quality Sensing Using AI-Based Frequency Selection
To enhance sensing accuracy, we implement AI-driven frequency selection using iterative linear regression and random forest models. A dataset of
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