vioft2nntf2t|tblJournal|Abstract_paper|0xf4ff9fb42e000000894f100001000700 The use of ML methods with the objective of selecting wheat varieties that have a higher level of rust resistance encoded in their genomes is referred to as rust selection. In addition to that, the categorization of wheat illnesses by means of machine learning It has been attempted to classify wheat diseases by making use of a wide variety of machine learning techniques. In this paper, we develop an enhanced deep learning model to classify the disease present in the wheat plant. The study uses an improved convolutional neural network to classify the plant disease using a series of layers. The simulation is conducted in terms of the accuracy, precision, recall and f-measure. The results show that the proposed method achieves higher rate of accuracy than its predecessor.
C. Kiran Kumar1, R. Gayathri2, S. Thirukumaran3, P.T. Kalaivaani4
Codecraft Technologies, Bangalore, Karnataka, India1, Rajalakshmi Engineering College, India2, Jain University, India3, Vivekanandha College of Engineering for Women, India4
ML, Wheat Varieties, Rust Resistance, Disease
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| Published By :
ICTACT
Published In :
ICTACT Journal on Image and Video Processing
( Volume: 13 , Issue: 2 , Pages: 2811 - 2816 )
Date of Publication :
November 2022
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