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I am working on detection of regions of specific tree in an aerial image and my approach is using texture detection. I have 4 descriptors/features and I want to use FANN to create a machine learning environment that would detect properly the regions.

My question is, is the format I am reading, regarding the input of pyfann, always as described in https://stackoverflow.com/a/25703709/5722784 ?

What if I would like to have 4 input neurons and one output neuron, where for each input neuron I have a list (not a single integer) that I would like to feed on it? Can FANN provide it? If so, what's the format that I have to follow in making the input data?

Thank you so much for significant responses :)

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Each input neuron can only take a single input - this is the case for all neural networks, irrespective of the library you use. I would suggest using each element in each of your lists as an input to the neural network, e.g. inputs 1-5 are your first list and then 6-10 are your second list. If you have variable length lists you likely have a problem, though.

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  • would "e.g. inputs 1-5 are your first list and then 6-10 are your second list." affect the learning of the machine? i mean, 1-5 describes a feature different from 6-10, is there a way I could tell the machine learning environment regarding that setup? or I leave it to the learning? – htinez Oct 11 '16 at 01:59