| Paper ID | MLSP-28.1 |
| Paper Title |
IN SITU CALIBRATION OF CROSS-SENSITIVE SENSORS IN MOBILE SENSOR ARRAYS USING FAST INFORMED NON-NEGATIVE MATRIX FACTORIZATION |
| Authors |
Olivier Vu thanh, University of Mons, Belgium; Matthieu Puigt, Farouk Yahaya, Gilles Delmaire, Gilles Roussel, Univ. Littoral Côte d'Opale, France |
| Session | MLSP-28: ML and Time Series |
| Location | Gather.Town |
| Session Time: | Thursday, 10 June, 14:00 - 14:45 |
| Presentation Time: | Thursday, 10 June, 14:00 - 14:45 |
| Presentation |
Poster
|
| Topic |
Machine Learning for Signal Processing: [MLR-MFC] Matrix factorizations/completion |
| IEEE Xplore Open Preview |
Click here to view in IEEE Xplore |
| Virtual Presentation |
Click here to watch in the Virtual Conference |
| Abstract |
In this paper, we assume a set of mobile geolocalized sensor arrays observing an area over time. Each of these arrays consists of heterogeneous and cross-sensitive sensors, i.e., the sensor readings provided by one of such sensors also depends on the readings of the other sensors in the array. We further assume that such arrays are possibly-uncalibrated and we aim to propose an in situ calibration method---i.e., a data-driven technique---for such arrays. The novelty of this paper is twofold: we first revisit in situ calibration of mobile cross-sensitive sensors as an informed factorization of a partially observed non-negative matrix. A fast informed (semi-)NMF approach is then proposed and found to be well-suited for the considered problem. |
