Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: ,  assume several heterogeneous, geolocalized, and time-stamped sensors to observe an area over time.  also assume that most of them are uncalibrated and  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 ighted 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.
['Clément Dorffer', 'Matthieu Puigt', 'Gilles Delmaire', 'Gilles Roussel']
I am writing a research paper on a idea Blind Calibration of Mobile Sensors Using Informed Nonnegative Matrix Factorization
[{"from": "human", "value": "I am writing a research paper on a idea Blind Calibration of Mobile Sensors Using Informed Nonnegative Matrix Factorization"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: ,  assume several heterogeneous, geolocalized, and time-stamped sensors to observe an area over time.  also assume that most of them are uncalibrated and  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 ighted 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."}]