R Jeevitha

KPR Institute of Engineering and Technology, Institute of Engineering

Papers

Total Citations

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About

R Jeevitha is a researcher at the forefront of applying artificial intelligence to agricultural challenges, with a particular focus on deep learning and embedded systems for plant science. Her most impactful work introduces the implementation of YOLOv9, a state-of-the-art object detection model, for enhanced weed detection in agricultural settings. This contribution, which has already garnered 6 citations since its 2024 publication, addresses the critical need for early and accurate weed identification to reduce crop yield losses and production costs. By leveraging advanced AI, Jeevitha provides farmers with a powerful tool for precision weed management. In earlier work, she explored the identification of plant species using embedded technology and MATLAB, demonstrating how image processing of leaf characteristics can enable automated plant classification. This foundational research, with 2 citations, showcases her versatility in bridging hardware and software solutions for agricultural automation. Jeevitha’s work is notable for its practical, real-world applications, directly supporting sustainable farming through intelligent, data-driven technologies. Her research continues to inspire students and professionals interested in the intersection of AI, computer vision, and agritech innovation.