MUMBAI, India, Aug. 17 -- Intellectual Property India has published a patent application (202621076549 A) filed by G. H. Raisoni College Of Engineering And Management; and Ghr Labs And Research Centre on June 20, 2026, for An Ensemble Machine Learning Based Crop Disease Detection System And Method Thereof.
Inventors include Anushree Wasudeo Wagde; Vansh Shyam Karande; Rohit Krushna Yeskar; Chetan Dnyaneshwar Talwekar; and Durgesh Ramesh Siriya.
The application for the patent was published on August 14, 2026, under issue no. 33/2026.
Abstract: ABSTRACT AN ENSEMBLE MACHINE LEARNING BASED CROP DISEASE DETECTION SYSTEM AND METHOD THEREOF The present invention relates to an ensemble machine learning based crop disease detection system configured for identifying plant diseases using digital images of crop leaves. The invention comprises an image acquisition module, an image preprocessing module, a segmentation module, a feature extraction module, an ensemble classification engine, and a display interface. The system acquires crop leaf images using digital imaging devices and performs preprocessing operations including resizing, filtering, contrast enhancement, and color space conversion. Diseased portions of leaves are isolated using segmentation techniques, followed by extraction of color, texture, and shape features. The extracted features are processed through an ensemble classifier comprising Support Vector Machine and Random Forest algorithms for accurate disease identification. The system generates real-time disease classification outputs along with treatment recommendations. The invention provides high accuracy, low computational complexity, reduced dependency on expert diagnosis, and reliable operation under varying environmental conditions, thereby supporting precision agriculture and sustainable farming practices. [To be published along with Figure 1]
Disclaimer: Curated by HT Syndication.
