Keras to extract quantitative information from images? (Physics research software)
I am currently working on an undergraduate research project designing software for a physics lab. The software currently takes microscopic images of particles obtained in the lab, and uses physics based algorithms to automatically extract qualitative data from the images. This data includes the particle diameter, and it's refractive index. The downside of the software is that it is very slow, and computation heavy due to the physics algorithms in place. So I had an idea. I am under the impression that a CNN, via Keras, should be able to identify features of interest (localization) and analyze them (regression) in one shot, or at least in one clean cascade of similar components. I haven't worked much with ML, and am wondering if someone more experience/knowledge might know if this sounds possible. If so, any leads on how to proceed, or any pointers relevant research papers, etc. would be appreciated.
The following stackexchange discussion explains how to get a number (such as particle diameter) from a network created with Keras: (I've been referencing this) https://stats.stackexchange.com/questions/243578/how-to-get-continuous-output-with-convolutional-network-keras
submitted by /u/curmudgeono