A novel approach using hybrid deep features for citrus disease detection and classification based on NCA and Bayesian optimised random forest classifier
by Shailesh Gondal; Shweta Agrawal
International Journal of Services, Economics and Management (IJSEM), Vol. 15, No. 5, 2024

Abstract: In this paper, deep features are retrieved from the citrus disease image gallery dataset using the AlexNet convolutional neural network. After data augmentation, the image dataset is sent for data pre-processing, where colour moments, GLCM, and Gabor wavelets are used to extract the colour feature and texture. Hybrid features are created by combining colour, texture, and deep characteristics. For feature selection, neighbourhood component analysis (NCA) is employed. The model's classification capabilities were also evaluated with those of the random forest classifier architecture for citrus disease detection in case 1 images and the Bayesian optimised random forest classifier architecture for citrus fruit disease detection in case 2 images. On a benchmark dataset including images of four distinct illnesses and healthy citrus fruit classes, the model performances were discovered. The dataset was identified using the disease image dataset with a maximum accuracy rate of 95.07%.

Online publication date: Wed, 04-Sep-2024

The full text of this article is only available to individual subscribers or to users at subscribing institutions.

 
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.

Pay per view:
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.

Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Services, Economics and Management (IJSEM):
Login with your Inderscience username and password:

Username:        Password:          Forgotten your password?

Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.

If you still need assistance, please email subs@inderscience.com