  Our recent study using historic data of paddy yield and associated conditions
include humidity, luminescence, and temperature. By incorporating regression
models and neural networks (NN), one can produce highly satisfactory
forecasting of paddy yield. Simulations indicate that our model can predict
paddy yield with high accuracy while concurrently detecting diseases that may
exist and are oblivious to the human eye. Crop Yield Prediction Using
Regression and Neural Networks (CYPUR-NN) is developed here as a system that
will facilitate agriculturists and farmers to predict yield from a picture or
by entering values via a web interface. CYPUR-NN has been tested on stock
images and the experimental results are promising.
