Intellectual Property India Publishes Patent Application for 'An Extensive Meta Analytical Review Of (VIT)Vision Transformer Paradigms For Automated Plant Leaf Disease Detection' Filed by Hlndusthan College Of Engineeering And Technology

MUMBAI, India, May 29 -- Intellectual Property India has published a patent application (202641043707 A) filed by Hlndusthan College Of Engineeering And Technology, Coimbatore, Tamil Nadu, on April 6, for 'an extensive meta analytical review of (vit)vision transformer paradigms for automated plant leaf disease detection.'

Inventor(s) include S. Shankar,; S. Rajesh Kannan; T. Yuvaraj; S. Shankar; N. J. R. Muniraj; K. Lakshmanan; S. Sathya; T. K. P. Rajagopal; D. Logana Than; P. Ra Vikumar; M. Vinitha; and S. S. Trilochan.

The application for the patent was published on May 29, under issue no. 22/2026.

According to the abstract released by the Intellectual Property India: "The present invention discloses a comprehensive meta-analytical framework based on Vision Transformer (ViT) paradigms for automated plant leaf disease detection. The system leverages transformer-based deep learning architectures to improve accuracy, scalability, and generalization in plant disease classification tasks. The proposed framework integrates multiple ViT variants, preprocessing pipelines, and benchmarking techniques to evaluate disease detection performance across diverse datasets. The system demonstrates superior accuracy, robustness to noise, and improved feature extraction compared to traditional convolutional neural networks (CNNs). Key outcomes include: * Enhanced classification accuracy across multi-crop datasets * Improved generalization under varying environmental conditions * Reduced dependency on manual feature engineering * Scalable architecture adaptable to real-time agricultural applications The invention can be applied m preciSion agriculture, smart farming systems, and automated crop monitoring solutions."

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