Dhanush Parasa

Papers

Total Citations

H-Index

About

Dhanush Parasa is a researcher at the forefront of applying artificial intelligence to agricultural technology. His most-cited work, "Detection of Tomatoes Using Artificial Intelligence Implementing Haar Cascade Technique" (2020), demonstrates a focused contribution to computer vision in precision farming. By leveraging the Haar cascade algorithm, Parasa developed a method for automated tomato detection, addressing key challenges in crop monitoring and yield estimation. This foundational study, with 4 citations, has provided a practical framework for integrating AI into real-time agricultural systems, particularly for fruit recognition tasks. Parasa’s research bridges the gap between machine learning and sustainable farming, offering scalable solutions that reduce manual labor and improve efficiency. His work is especially relevant for students and researchers exploring edge AI and embedded vision in agriculture. While early in his career, Parasa’s targeted application of classical AI techniques highlights the enduring value of robust, computationally efficient algorithms in resource-constrained environments. His contributions underscore the potential of AI to transform traditional industries, making him a promising voice in the intersection of technology and food security.