UJIIndoorLoc: A new multi-building and multi-floor database for WLAN fingerprint-based indoor localization problems

By Joaquín Torres-Sospedra, Raúl Montoliu, Adolfo Martínez Usó, Joan P. Avariento, Tomas J. Arnau, Mauri Benedito-Bordonau, Joaquín Huerta. 2014

546 citations recorded by the source corpus.

Subfields: Aerospace Engineering, Electrical and Electronic Engineering, Ocean Engineering

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Aerospace Engineering

1. Eric P. Xing
2. Ming Ding
3. Barnab'as P'oczos
4. Jeff Schneider
5. Dinh C. Nguyen
6. F. I. H. Vincent Poor
7. Willie Neiswanger

In Electrical and Electronic Engineering

1. Dinh C. Nguyen
2. Pubudu N. Pathirana
3. Eric P. Xing
4. Aruna Prasad Seneviratne
5. Jun Li
6. Ming Ding
7. Barnab'as P'oczos
8. Jeff Schneider

In Ocean Engineering

1. Eric P. Xing
2. Barnab'as P'oczos
3. Jeff Schneider
4. Dinh C. Nguyen
5. Kirthevasan Kandasamy
6. Willie Neiswanger

Citations in the corpus

• Neural Architecture Search with Bayesian Optimisation and Optimal Transport (2018, methodology): “Datasets: We use the following datasets: blog feedback [4], indoor location [43], slice localisation [11], naval propulsion [5], protein tertiary structure [31], news popularity [7], Cifar10 [21].”
• Federated Learning for Internet of Things: A Comprehensive Survey (2021, methodology): “By using available RSS data from UJIIndoorLoc database [89], a simulation is performed for the proposed FL scheme, showing a significant improvement in the localization accuracy while privacy is preserved in different indoor settings.”