What will be the suitable network to train on size of grains in an image? Inputs will be images (64x64 or higher order 256x256) and output should be number float (size of particles in image). I prepared a dataset using voronoi cells.
I looked into the digits recognition problem but that seemed classification problem (categories of 10 digits). So in examples it was using MLPclassifier or CNN( categorial loss and softmax in final layer.)
mrpacetv t1_iz98n4y wrote
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What will be the suitable network to train on size of grains in an image?
Inputs will be images (64x64 or higher order 256x256) and output should be number float (size of particles in image). I prepared a dataset using voronoi cells.
I looked into the digits recognition problem but that seemed classification problem (categories of 10 digits). So in examples it was using MLPclassifier or CNN( categorial loss and softmax in final layer.)