java - how to give image input to neural network for pattern recognition -


i working on pattern recognition of plant disease image using propagation neural network(in java). knew different binary features can given input neural network. totally confuse how compare output of neural network in scenario. mean not have output defined. , in case of image how can define output can find error between defined out , calculated output network adjust weight.i serious, please me. thank

this no means complete answer, not fit in comment box. should provide guidance could do.

what encode image series of byte values ranging [0,255]. should yield vector of bytes size should same amount of pixels within image.

you pass on vector neural network, meaning input layer of neural network need big vector itself.

lastly, assign different vector values denote different diseases. instance, given input vector [1,55,201,44,258,...] expected vector [0,0,0,0,0,1]. vector map particular disease.

if colour not important you, reduce input vector vector of binary values, where, turn image black , white instance, according threshold.


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