Majid Sorouri

Islamic Azad University, Science and Research Branch

Papers

Total Citations

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About

Majid Sorouri is a rising researcher at the intersection of agricultural robotics and deep learning, whose work focuses on automating critical tasks in precision agriculture. His most impactful contribution involves the early detection of plant diseases using artificial intelligence, specifically targeting powdery mildew in apple tree leaves. In his 2023 study, Sorouri demonstrated how deep learning models can process leaf images to diagnose this common pest with high accuracy, a breakthrough that enables intelligent sprayer robots to apply treatments only where needed, reducing chemical usage and labor. This work, which has already garnered 5 citations, addresses the urgent need for scalable, non-invasive crop monitoring. Beyond disease detection, Sorouri has also contributed to the design of automated planting systems, developing a CNC-controlled seedling planting robot capable of rapidly reforesting damaged areas—a solution to the labor-intensive process of large-scale planting. His research sits at the nexus of computer vision, mechatronics, and sustainable agriculture, offering practical tools for farmers and environmental restoration projects. With a focus on real-world deployment, Sorouri’s work is paving the way for smarter, more efficient agricultural practices.