• PRABIRA KUMAR SETHY
• SHRADDHANJALI SATPATHY
• SANTI KUMARI BEHERA
• GYANA RANJAN PANIGRAHI

Rice grain identification is a challenging research in current time, as many young farmer unable to identify many species of rice by observing its external appearance. This paper develop a novel model based on Bayesian regularization of artificial neural network (BRANN) using texture feature of rice grain. The model is develop using 13 input neuron, 15 hidden neuron & 6-output neuron and achieve predictive correlation, R of 0.93, which is quit high, leads a reliable model for identification of rice grain.

Rice grain identification, geometrical feature, image processing, Bayesian regularization.

"Rice Grain Identification Model based on Bayesian Regularization of Artificial Neural Network using Geometrical Feature", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 5, page no.538-542, May-2019, Available :http://www.jetir.org/papers/JETIR1905682.pdf

"Rice Grain Identification Model based on Bayesian Regularization of Artificial Neural Network using Geometrical Feature", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 5, page no. pp538-542, May-2019, Available at : http://www.jetir.org/papers/JETIR1905682.pdf