What you’re aiming is actually more like a “high-level” classification, in which you’d combine many “low-level” features like pixel intensity, textural parameters etc… to distinguish neutrophils and keratinocytes.
Thinking in this way, CellProfiler only can provide to you the materials at low level, i.e. CellProfiler pipeline won’t be able to help you to immediately “segment” separately these 2 difficult cell types straight out-of-the-box.
So, I suggest you first just try to build a pipeline to segment correctly ALL cells in the pictures, and measure ALL features you could think of, like intensity, texture, size, shape, granularity, distribution etc…
You’ll then bring these materials into some form of machine learning to do the classification.
One of the ways is using CPA as you’ve mentioned, where you’d train a “Classifier”, i.e. hand-annotate which cell is which by drag-and-drop them into different bins. And hopefully one of the model can do the classification for you accurately.
Please have a look here
Hope that helps.