Wenqiang Hua | Deep Learning | Research Excellence Award

Dr. Wenqiang Hua | Deep Learning | Research Excellence Award

Xi’an University of Posts and Telecommunications | China

Wenqiang Hua is a Lecturer in the School of Computer Science at Xi’an University of Posts and Telecommunications and a member of the Key Laboratory of Big Data and Intelligent Computing. He holds a Ph.D. in Electronic Circuits and Systems with a strong research focus on deep learning, image classification, and remote sensing image analysis, particularly Polarimetric SAR image classification. His work emphasizes semi-supervised learning, contrastive learning, domain adaptation, feature fusion, and multi-modal neural networks for complex remote sensing scenarios. Dr. Hua has published extensively in leading international journals, including IEEE Geoscience and Remote Sensing Letters, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Remote Sensing, Knowledge-Based Systems, and the International Journal of Applied Earth Observation and Geoinformation. He has also led nationally and provincially funded research projects related to small-sample PolSAR terrain classification. Known for his extroverted, optimistic, and enthusiastic character, he actively engages in interdisciplinary research and academic collaboration.

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Featured Publications


Knowledge and Data Co-Driven Deep Learning Model for PolSAR Image Classification

– Results in Engineering

Class-Discrepancy Dynamic Weighting for Cross-Domain Few-Shot Hyperspectral Image Classification

– Remote Sensing

Semi-Supervised Hybrid Contrastive Learning for PolSAR Image Classification

– Knowledge-Based Systems

Global–Local Multigranularity Transformer for Hyperspectral Image Classification

– IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing