Fatimah Asmita Rani

Papers

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About

Fatimah Asmita Rani is a researcher at the intersection of computer vision and agricultural technology, with a primary focus on intelligent plant disease detection. Her most cited work, "K-means Clustering and SVM for Plant Leaf Disease Detection and Classification" (2019, 27 citations), addresses a critical challenge in precision agriculture: the automated identification of leaf diseases. Rani’s contribution lies in integrating K-means clustering for segmentation with Support Vector Machines (SVM) for classification, establishing a robust pipeline that enhances detection accuracy. By emphasizing the role of image preprocessing—specifically color median filtering—she improved the quality of input data for subsequent analysis. This work has been influential in demonstrating how classical machine learning techniques can be effectively applied to agricultural diagnostics, offering a cost-effective alternative to deep learning approaches. Her research underscores the broader applicability of computer vision in fields ranging from robotics to medicine, but her specific focus on plant pathology has made her a notable figure in the agricultural AI community. With 27 citations, this paper remains a foundational reference for researchers developing scalable, real-time disease monitoring systems for crop management.