I am new to ML and have some experience with building CNN models. I recently got involved with a research project and here is the task I have to work on:
I've been given some (latitudes,longitudes) points with cellular signal strength(float numbers) on those particular points. And I've been given the location, (lat,longs) of cellular towers in a particular area. Also I've been given the terrain data, i.e. the (latitude,longitude) locations of areas where there are buildings, trees, hills etc. that can cause disruption of signals.
I have to predict the signal strengths for new areas given all this data(terrain data and tower sites). Basically, the signal strength will depend on the nearby areas(i.e. if they are hills or buildings or trees and so on) and how close a tower is to a particular point.
I've been trying to find a model for this for a week now with no apparent progress. The problem is that every model I've seen(CNNs, Variational Autoencoders, GANs) take in the image data and produce image data. What I have to do is predict numerical values of signal strengths on a map using the image(terrain) data. Any ideas which model can be used?