Shantam Shorewala
Papers
1
Total Citations
106
H-Index
1
About
Shantam Shorewala is a researcher at the intersection of computer vision, machine learning, and precision agriculture, with a particular focus on applying deep learning techniques to real-world agricultural challenges. His most recognized work, "Weed Density and Distribution Estimation for Precision Agriculture Using Semi-Supervised Learning" (2021), has garnered an impressive 106 citations, reflecting its significant influence in the field. In this study, Shorewala tackled the critical problem of uncontrolled weed growth, which threatens crop yield and quality, by developing a semi-supervised learning framework capable of identifying and estimating weed-infested regions. This approach enables selective herbicide application, reducing environmental pollution and preserving biodiversity — a meaningful step toward sustainable farming practices. His work elegantly bridges the gap between advanced machine learning methodologies and pressing agricultural needs, demonstrating how artificial intelligence can drive smarter, more responsible land management. For students and researchers exploring AI-driven solutions in agriculture or environmental sustainability, Shorewala's contributions offer both a technically rigorous and practically impactful body of work worth careful study.
Research Focus
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Top Papers
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