Gulbahar Tohti

Papers

Total Citations

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About

Gulbahar Tohti is a researcher specializing in agricultural automation and computer vision, with a particular focus on the mechanized harvesting of medicinal plants. Her work centers on developing lightweight, efficient deep learning models for real-time crop detection, specifically targeting marigold—a valuable traditional Chinese medicine known for its liver-protective and anti-inflammatory properties. Tohti’s major contribution is an improved YOLOv7 lightweight detection model for marigold corollas, which enhances the accuracy and speed of identifying harvest-ready flowers in complex field environments. This innovation directly addresses the growing demand for mechanized harvesting as marigold cultivation expands. Her most cited paper, published in 2024, has already garnered 13 citations, demonstrating its immediate relevance to the agricultural AI community. By optimizing object detection for resource-constrained devices, Tohti’s work bridges the gap between advanced computer vision and practical farming needs, offering a scalable solution for automating the harvest of medicinal crops. Her research not only advances precision agriculture but also supports the sustainable production of traditional medicines, making her a notable contributor to the intersection of AI and agronomy.