Weiwei Zhang

Shanghai University of Engineering Science

Papers

Total Citations

104

H-Index

About

Weiwei Zhang is a leading researcher in computer vision and intelligent transportation systems, with a particular focus on deep learning for real-time object recognition and classification. Zhang’s most-cited work, "Real-time vehicle type classification with deep convolutional neural networks" (2017, 104 citations), introduced a novel framework that combines deep convolutional neural networks with efficient processing pipelines to achieve high-accuracy vehicle classification in dynamic traffic environments. This contribution has been instrumental in advancing smart city infrastructure, enabling automated toll collection, traffic monitoring, and security surveillance systems. By addressing the critical challenge of balancing computational efficiency with classification precision, Zhang’s research has provided a foundational methodology for real-time visual analytics in resource-constrained settings. The paper’s sustained citation count reflects its practical impact on both academic research and industrial applications, influencing subsequent work in fine-grained object categorization and embedded vision systems. Zhang’s work continues to shape the development of autonomous driving technologies and intelligent transportation networks, demonstrating a commitment to bridging the gap between theoretical deep learning advances and deployable real-world solutions.