MUMBAI, India, Oct. 5 -- Intellectual Property India has published a patent application (202641115366 A) filed by Sri Eshwar College Of Engineering on September 24, 2026, for Performance Analysis Of Tea Leaf Disease Detection By Utilizing Vgg16 And Birnn.
Inventors include Dr. N. Muthukumaran; and Dr. S. Ram Kumar.
The application for the patent was published on October 02, 2026, under issue no. 40/2026.
Abstract: Tea leaf disease detection is a crucial task in the agriculture industry, where timely and accurate identification of leaf conditions can lead to better crop management and yield. Traditional methods of leaf disease detection are often time-consuming and subjective, relying on manual inspections that are not scalable in large tea plantations and are prone to human error. With advancements in deep learning, this study proposes a hybrid model combining VGG16 and Bidirectional Recurrent Neural Network (BiRNN) networks for enhanced performance in tea leaf detection. The VGG16 component extracts robust spatial features from images, while BiRNN captures sequential dependencies within these features to refine the classification accuracy and model interpretability. The proposed solution aims to enhance agricultural productivity by enabling early and accurate detection of diseases in tea leaves using deep learning techniques. By automating the disease classification process, the system reduces the dependency on manual inspection, minimizes crop loss, and supports informed decision-making for farmers. This project aligns with Sustainable Development Goal 9: Industry, Innovation, and Infrastructure and SDG 12: Responsible Consumption and Production, as it encourages the adoption of innovative technologies in agriculture while ensuring sustainable resource usage. Currently, the system stands at Technology Readiness Level 3 (Analytical and experimental proof of concept), indicating that the concept has been demonstrated in a controlled research environment, with plans for further development and field-level validation.
Disclaimer: Curated by HT Syndication.
