Pavan Dasari

Papers

Total Citations

H-Index

About

Pavan Dasari is a computer vision and deep learning researcher whose work focuses on advancing human action recognition for real-world applications. His most-cited paper, "Human Action Recognition Using Hybrid Deep Evolving Neural Networks" (2022, 18 citations), introduces a novel hybrid architecture that combines evolving neural networks with deep learning to improve the accuracy and adaptability of action recognition systems. This work addresses critical challenges in domains such as large-scale surveillance, threat detection, personal safety in hazardous environments, human assistance, health monitoring, and intelligent robotics. Dasari’s contributions are particularly notable for their emphasis on real-time, robust performance in dynamic and uncontrolled settings, bridging the gap between theoretical deep learning models and practical deployment. His research has been cited by peers working on video understanding, edge computing, and assistive technologies, reflecting its interdisciplinary impact. By tackling the high demands of real-world applications—from security to healthcare—Dasari continues to push the boundaries of how machines interpret and respond to human behavior, making his work essential reading for students and researchers in computer vision and intelligent systems.