Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Faculty Publications Conference Paper Faculty Publications- Conference Papers Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Creator An entity primarily responsible for making the resource Prashant, C.; Acharya, Biswaranjan; Vijaya, P.; Bejoy, B.J.; Raju, G.; Singh, Ajay Vikram Title A name given to the resource Machine Learning Models for Apple Disease Detection With Texture Feature Fusion and Feature Selection Date A point or period of time associated with an event in the lifecycle of the resource 01-01-2025 Source A related resource from which the described resource is derived 2025 12th International Conference on Reliability, Infocom Technologies and Optimization ,Trends and Future Directions, ICRITO 2025; Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1109/ICRITO66076.2025.11241915" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/ICRITO66076.2025.11241915</a> <br /><br /><a href="https://www.scopus.com/pages/publications/105029839218?origin=resultslist" target="_blank" rel="noreferrer noopener">https://www.scopus.com/pages/publications/105029839218?origin=resultslist</a> Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Prashant C., Christ University, Bengaluru, India; Acharya B., Marwadi University, Department of AI, Ml and Ds, Rajkot, India; Vijaya P., Modern College of Business and Science, Department of Mathematics and Computer Science, Bowshar, Muscat, Oman; Bejoy B.J., Christ University, Bengaluru, India; Raju G., Sahrdaya College of Engineering and Technology, Kerala, Thrissur, India; Singh A.V., Aiit, Amity University, Uttar Pradesh, India Description An account of the resource Computer vision has become an integral part of modern agriculture. One of the key applications of Computer vision is the automatic detection and classification of plant disease from digital images of plant leaves. In this study we evaluate the discriminatory capability of selected texture features and their fusion in identifying plant diseases from leaf images. Further, the performance of four feature selection algorithms is also evaluated. Texture features are extracted from resized raw images. Experiments are carried out with public data sets of Apple plants. Through extensive experimentation, two classifiers - Random forest and XGBoost are chosen for the evaluation. The feature fusion and feature selection resulted in 85% accuracy. The result is promising as the features are extracted from whole leaf images, without any segmentation. 2025 IEEE. Subject The topic of the resource Apple diseases; Boruta; feature fusion; LDA; PCA; Random Forest; ReliefF; texture features; XGBoost Publisher An entity responsible for making the resource available Institute of Electrical and Electronics Engineers Inc. Relation A related resource ISBN: 979-833155421-7; Language A language of the resource English Type The nature or genre of the resource Conference paper Rights Information about rights held in and over the resource Restricted Access; Hardcopy may be available in the library Format The file format, physical medium, or dimensions of the resource online