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LEAVES RECOGNITION USING BACK PROPAGATION NEURAL NETWORK-ADVICE FOR PEST & DISEASE CONTROL ON CROPS.

 

*M. S. Prasad Babu & B.Srinivasa Rao.

 

*Professor of Computer Science & Systems Engineering
Andhra University, Visakhapatnam-AP-India-530 003.

 

KEYWORDS

 
AGRICULTURE – CROPS—PLANTS –LEAVES – PEST IMAGES RECOGNITION BACK PROPAGATION NEURAL NETWORKS—CONTROL MEASURES.
 

ABSTRACT

 

The main goal of this paper is to develop a software model, to suggest remedial measures for pest or disease management in agricultural crops. Using this software, the user can scan an infected leaf to identify the species of leaf, pest or disease incidence on it and can obtain solutions for its control. The software system is divided into modules namely: Leaves Processing, Network Training, Leaf Recognition, and Expert advice. In the first module edge of the leaf and token values found. The Second module deals with the training of the leaf to the neural network and finding the error graph. The third and fourth modules are to recognize the species of the leaf and identify the pest or disease incidence. The last module is aimed at matching the recognized pest or disease sample on to the database where in pest-disease image samples and correcting remedial measures for their management are stored.
 

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