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A Hybrid Framework Integrating Novel Segmentation and Hybrid Feature Engineering with M-SVM for the Detection and Classification of Wheat Rusts and Septoria Cover

A Hybrid Framework Integrating Novel Segmentation and Hybrid Feature Engineering with M-SVM for the Detection and Classification of Wheat Rusts and Septoria

Foundations of Computing and Decision Sciences
Volume 51 (2026): Issue 2 (June 2026)
By:  and    
Open Access
|Jun 2026
Articles in this issue
DOI: https://doi.org/10.2478/fcds-2026-0009 | Journal eISSN: 2300-3405 | Journal ISSN: 0867-6356
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Language: English
Page range: 259 - 310
Submitted on: Nov 1, 2025
Accepted on: Apr 14, 2026
Published on: Jun 26, 2026
Published by: Poznan University of Technology
In partnership with: Paradigm Publishing Services
Keywords:
Wheat Rusts and Septoria,
Adaptive K-Means Clustering,
Gaussian Mixture Model (GMM),
PCA,
Feature Extraction,
Multi-Class Support Vector Machine (M-SVM)
Related subjects:
Computer sciences,
Software development

© 2026 Ranjeet Singh, Dayashankar Singh, published by Poznan University of Technology
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Volume 51 (2026): Issue 2 (June 2026)
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