Researchers have introduced WhoFi, an AI-powered deep learning pipeline that leverages Wi-Fi Channel State Information (CSI) for person re-identification (Re-ID), achieving a remarkable 95.5% Rank-1 accuracy on the NTU-Fi dataset. Traditional visual Re-ID systems, reliant on convolutional neural networks (CNNs) and features like color histograms or Histograms of Oriented Gradients (HOG), falter under occlusions, varying […]The post AI-Driven Wi-Fi Biometrics WhoFi Tracks Humans Behind Walls with 95.5% Accuracy appeared first on GBHackers Security | #1 Globally Trusted Cyber Security News Platform.