Fungi Classification using Convolution Neural Network
Sukanya S. Gaikwad
Abstract
This paper presents a model based on Convolution Neural Network (CNN) to identify and classify the fungi those causes disease to apple plant leaf. In this paper, apple scab, rust, black rot, and healthy leaf are studied and classified. The plant pathology dataset (publically available) consists of 9164 images are used for experimentation. The proposed CNN model identifies and classifies the apple leaves into these four categories. This model can successfully detect and classify diseases with an accuracy of 88.9%.
Topics & Concepts
Convolutional neural networkArtificial intelligencePlant diseaseConvolution (computer science)Computer scienceRust (programming language)Pattern recognition (psychology)Artificial neural networkBiologyBiotechnologyProgramming languageSmart Agriculture and AISpectroscopy and Chemometric Analyses