20 citations · 42 across the 12 of their papers we have counts for
4 papers · 1 filter
STELLAR: Siamese Multi-Headed Attention Neural Networks for Overcoming Temporal Variations and Device Heterogeneity with Indoor Localization
Danish Gufran, Saideep Tiku, Sudeep Pasricha
Smartphone-based indoor localization has emerged as a cost-effective and accurate solution to localize mobile and IoT devices indoors. However, the challenges of device heterogenei…
CALLOC: Curriculum Adversarial Learning for Secure and Robust Indoor Localization
Danish Gufran, Sudeep Pasricha
Indoor localization has become increasingly vital for many applications from tracking assets to delivering personalized services. Yet, achieving pinpoint accuracy remains a challen…
FedHIL: Heterogeneity Resilient Federated Learning for Robust Indoor Localization with Mobile Devices
Danish Gufran, Sudeep Pasricha
Indoor localization plays a vital role in applications such as emergency response, warehouse management, and augmented reality experiences. By deploying machine learning (ML) based…
VITAL: Vision Transformer Neural Networks for Accurate Smartphone Heterogeneity Resilient Indoor Localization
Danish Gufran, Saideep Tiku, Sudeep Pasricha
Wi-Fi fingerprinting-based indoor localization is an emerging embedded application domain that leverages existing Wi-Fi access points (APs) in buildings to localize users with smar…