Sankardas Kariparambil Sudheesh
Papers
1
Total Citations
11
H-Index
1
About
Sankardas Kariparambil Sudheesh is a researcher advancing the intersection of machine learning and agricultural technology. His primary research areas include computer vision, pattern recognition, and the application of support vector machines (SVMs) to environmental monitoring. His most cited work, "Coconut trees classification based on height, inclination, and orientation using MIN-SVM algorithm" (2023), introduces a novel approach to automating the classification of coconut trees by analyzing their physical attributes. This contribution is significant for precision agriculture, enabling efficient resource management and yield estimation in tropical farming systems. With over 11 citations for this single paper, Sudheesh’s work demonstrates clear impact in the field, offering a scalable solution for remote sensing and crop inventory. His research not only addresses practical challenges in agriculture but also showcases the potential of optimized machine learning algorithms for real-world applications. Sudheesh’s dedication to bridging computational methods with agricultural needs marks him as an emerging voice in applied AI, with future work likely to expand into broader environmental and ecological monitoring.
Research Focus
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Top Papers
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