J. R.

Vellore Institute of Technology University

Papers

Total Citations

H-Index

About

J. R. is a rising researcher in the field of precision agriculture and computer vision, with a primary focus on deep learning applications for crop and weed management. Their most notable contribution is the development of a Region-Based Convolutional Neural Network (RCNN) approach for weed detection in farmlands, a critical step toward optimizing herbicide use and reducing crop competition. This work, published in 2025, has already garnered 4 citations, signaling early impact in a rapidly evolving domain. By addressing the challenge of accurate species-level weed identification, J. R. helps bridge the gap between automated sensing and sustainable farming practices. Their research is particularly valuable for students and practitioners interested in integrating artificial intelligence with agricultural robotics and environmental stewardship.