In this paper, we assume several heterogeneous, geolocalized, and time-stamped sensors to observe an area over time. We also assume that most of them are uncalibrated and we propose a novel formulation of the blind calibration problem as a Nonnegative Matrix Factorization (NMF) with missing entries. Our proposed approach is generalizing our previous informed and weighted NMF method, which is shown to be accurate for the considered application and to outperform blind calibration based on matrix completion and nonnegative least squares.
CITATION STYLE
Dorffer, C., Puigt, M., Delmaire, G., & Roussel, G. (2015). Blind calibration of mobile sensors using informed nonnegative matrix factorization. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 9237, pp. 497–505). Springer Verlag. https://doi.org/10.1007/978-3-319-22482-4_58
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