Published September 18, 2023
| Version v1
Poster
Open
Optimal Sensor Placement for Black Carbon AOD with Convolutional Neural Processes (poster)
- 1. Image Processing Lab, Universitat de València
- 2. The Alan Turing Institute
- 3. British Antarctic Survey
Description
This poster showcases the results of a 3-month collaboration at The Alan Turing Institute, using convolutional neural processes via the open-source Python package DeepSensor to model black carbon aerosols from limited observations and propose optimal placements for new ground-based sensors.
Presented at the joint iMIRACLI Summer School / FORCeS annual meeting 2023 in Patras, Greece (18-22 September 2023).
Files
Pelucchi_2023_Optimal-Sensor-Placement-for-Black-Carbon-AOD-with-Convolutional-Neural-Processes_poster.pdf
Files
(2.3 MB)
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