Received signal strength (RSS) fingerprint-based indoor localization has received
increasing popularity over the past decades. However, it suffers from the high calibration …

Fingerprint-based indoor localization has drawn increasing attention with the development
of deep learning. Nevertheless, it faces challenges from frequent data collection and the …

This work aims at proposing a transfer learning (TL)-based framework to enhance system
scalability of fingerprint-based indoor localization by reducing offline training overhead …

Wireless Local Area Network (WLAN) location fingerprinting has become a prevalent
approach to indoor localization. However, its widespread adoption has been hindered by …

Recently, machine learning (ML) has been widely adopted for fingerprint-based indoor
localization because of its potency in delineating relationships between received signal …

Indoor positioning based on the received signal strength (RSS) of the WiFi signal has
become the most popular solution for indoor localization. In order to realize the rapid …

Deep learning-based Wi-Fi indoor fingerprint localization, which requires a large received
signal strength (RSS) dataset for training, has been widely studied. Federated learning (FL) …

Indoor localization using Received Signal Strength Indication (RSSI) fingerprinting has been
extensively studied for decades. The positioning accuracy is highly dependent on the …

Received Signal Strength (RSS) fingerprint-based localization has attracted a lot of research
effort and cultivated many commercial applications of location-based services due to its low …

Localization Based Service (LBS) has become as one of the most important applications in
modern daily life. Positioning technologies for outdoor environments are relatively mature …