IMPROVING MEDICAL IMAGE PROCESSING USING AN ENHANCED DEEP LEARNING ALGORITHM

C, Kiran Kumar and R, Gayathri and S, Thirukumaran and P.T., Kalaivaani (2022) IMPROVING MEDICAL IMAGE PROCESSING USING AN ENHANCED DEEP LEARNING ALGORITHM. ICTACT Journal on Image and Video Processing, 13 (2). pp. 2811-2816. ISSN 09769099

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Abstract

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.

Item Type: Article
Subjects: Electronics and Communication Engineering > Machine Learning for Signal Processing
Divisions: Electronics and Communication Engineering
Depositing User: Unnamed user with email techsupport@mosys.org
Date Deposited: 05 Oct 2026 05:34
Last Modified: 05 Oct 2026 05:34
URI: https://ir.vcenggw.ac.in/id/eprint/169

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