Classifying cereal grains using backpropagation and cascade correlation networks

This paper presents backpropagation- and cascade correlation-trained artificial neural networks for cereal grain classification. In comparison with a Gaussian classification technique, the neural networks deliver higher classification accuracy and are more attractive for implementation in automated grain inspection systems.