Peijun Xia

Papers

Total Citations

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About

Peijun Xia’s research lies at the intersection of computer vision, intelligent robotics, and embedded system security, with a particular focus on advancing face recognition technologies for real-world safety applications. In their most-cited work, "Face Recognition for Intelligent Robot Safety Verification System" (2017), Xia tackled a critical challenge: enabling resource-constrained embedded devices to perform accurate, real-time face recognition. By introducing a novel ResNet-based architecture optimized for limited computational resources, they addressed the dual problems of insufficient recognition accuracy and inadequate deep learning capacity in existing systems. This contribution directly enhances the security verification capabilities of intelligent robots, ensuring they can reliably identify authorized users. Although early in their citation trajectory, Xia’s work represents a foundational step toward safer human-robot interaction, demonstrating how efficient neural network design can bridge the gap between cutting-edge AI and practical deployment constraints. Their research continues to influence the development of lightweight, high-performance vision systems for autonomous platforms.