Huihui Sun Data-verified

OverviewAI-generated summary

Huihui Sun's research interests include the application of machine learning and deep learning techniques to address complex problems. Sun has published work on motion planning for mobile robots, utilizing deep reinforcement learning, and has investigated event-triggered reconfigurable reinforcement learning approaches for robots operating in dynamic environments. Additionally, Sun has contributed to the development of lightweight deep learning models for agricultural applications, such as a high-accuracy model for rice disease detection (RDRM-YOLO) and models for blueberry maturity recognition (BMDNet-YOLO) and tomato detection and quality assessment (ToRLNet).

Further research by Sun explores adaptive dictionary and structure learning for unsupervised feature selection. Sun's work also touches upon the use of neural networks in analyzing nonlinear dynamic processing within the context of big data for defense audits. Sun holds a h-index of 17 with 1,188 total citations across 37 publications and collaborates with researchers such as Gerson Laerson Drescher and Beatriz Moreno‐García.

Metrics

• h-index: 17
• Publications: 37
• Citations: 1,188