Name
Abstract | ||
|---|---|---|
Water monitoring systems continuously working ensure real–time pollutant detection capabilities according to their sensitivity and specificity. It is necessary to balance such features because, although being able to sense several substances is a desired feature, the reduction of false positives is a primary goal a classification system should have. High false positive makes the system unusable. T... |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1109/SMARTCOMP52413.2021.00065 | 2021 IEEE International Conference on Smart Computing (SMARTCOMP) |
Keywords | DocType | ISBN |
water quality monitoring,machine learning,false positive reduction | Conference | 978-1-6654-1252-0 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
13 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Alessandro Bria | 1 | 57 | 10.63 |
| Luigi Ferrigno | 2 | 202 | 34.29 |
| L. Gerevini | 3 | 0 | 0.34 |
| Claudio Marrocco | 4 | 84 | 17.53 |
| M. Molinara | 5 | 38 | 6.29 |
| Paolo Bruschi | 6 | 62 | 17.83 |
| M. Cicalini | 7 | 0 | 0.34 |
| G. Manfredini | 8 | 0 | 0.34 |
| A. Ria | 9 | 0 | 0.34 |
| g cerro | 10 | 15 | 8.18 |
| R. Simmarano | 11 | 0 | 1.35 |
| G. Teolis | 12 | 0 | 0.34 |
| M. Vitelli | 13 | 0 | 0.34 |