Yonghong Yu

Nanjing University of Posts and Telecommunications

Papers

Total Citations

128

H-Index

About

Dr. Yonghong Yu is a leading researcher in intelligent systems, specializing in human action recognition and sound classification through advanced deep learning and optimization techniques. Her work centers on developing evolving ensemble models that integrate deep neural networks with swarm-based optimization algorithms, notably Particle Swarm Optimization, to create adaptive, high-performance recognition systems. Her most influential contributions include an ensemble model for intelligent human action recognition (59 citations) and a sound classification framework using evolving ensembles (51 citations), both published in 2021. These innovations address critical challenges in real-world applications such as surveillance, threat detection, personal safety, health monitoring, and intelligent robotics. Dr. Yu’s 2022 work on hybrid deep evolving neural networks for human action recognition further demonstrates her commitment to pushing the boundaries of adaptive AI. With over 128 citations across her top papers, her research is widely recognized for its practical impact, offering robust solutions for dynamic environments where traditional static models fall short. Her achievements underscore a career dedicated to bridging cutting-edge optimization and deep learning for real-time, intelligent decision-making.