Name
Title | ||
|---|---|---|
POSEIDON: An Analytical End-to-End Performance Prediction Model for Submerged Object Detection and Recognition by Lidar Fluorosensors in the Marine Environment. |
Abstract | ||
|---|---|---|
An analytical end-to-end model is developed to predict the performance of underwater object recognition by means of light detection and ranging (lidar) fluorosensors, as an aid to underwater lidar mission planning and system design. The proposed Performance prediction mOdel for Submerged object dEtection and recognitIon by liDarfluOrosensors in the marine eNvironment (POSEIDON) reproduces the over... |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1109/JSTARS.2017.2737645 | IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing |
Keywords | Field | DocType |
Laser radar,Laser beams,Object detection,Predictive models,Backscatter,Signal processing,Water | Object detection,Signal processing,Computer vision,Remote sensing,Bathymetry,Lidar,Artificial intelligence,Performance prediction,Spectral signature,Mathematics,Underwater,Cognitive neuroscience of visual object recognition | Journal |
Volume | Issue | ISSN |
10 | 11 | 1939-1404 |
Citations | PageRank | References |
0 | 0.34 | 14 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Stefania Matteoli | 1 | 152 | 18.05 |
| Laura Zotta | 2 | 3 | 1.23 |
| Marco Diani | 3 | 261 | 30.99 |
| Giovanni Corsini | 4 | 299 | 40.26 |