Research article

TRANSFER LEARNING APPROACH FOR PLANT DISEASE DIAGNOSIS IN PADDY CROPS WITH SMALL DATASET AND COMPLEX IMAGE BACKGROUND

Ashima Kalra, Gaurav Tewari, Bhawna Tandon

Online First: December 30, 2022


Rice is one of the important and preferable grains among agricultural crops but it is susceptible to various viral, bacterial and fungal diseases. Various Deep CNN model has been implemented to diagnose such diseases. But many times, the lack of plant leaf picture datasets that can portray the wide range of symptoms and circumstances of features observed in reality is the main problem in using Deep CNN to automatically identify crop diseases. In this paper, we have discussed about a proposed transfer learning model which can deal these issues effectively. Transfer learning model learns the significant features so deeply and nicely that it gives promising result even for unprocessed input data.

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