Xiao Kong

Papers

Total Citations

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About

Dr. Xiao Kong is a researcher at the forefront of intelligent manufacturing and industrial automation, with a focus on integrating advanced computer vision into quality control processes. His work directly supports the goals of "Made in China 2025" and Industry 4.0, addressing critical challenges in smart workshop design. Dr. Kong’s most notable contribution is the development of the "Improved SSD for Door Panel Missed Installations Inspection Using PASSD," a novel approach that enhances the accuracy of object detection for automated defect identification. This method tackles the inefficiencies of traditional manual inspection—which is time-consuming, inconsistent, and error-prone—by leveraging a refined Single Shot MultiBox Detector (SSD) architecture. While his 2023 paper has garnered 2 citations, its practical implications for reducing production errors and improving throughput in automotive manufacturing are significant. Dr. Kong’s research bridges the gap between theoretical computer vision and real-world industrial applications, offering scalable solutions for intelligent workshops. His work is particularly valuable for students and engineers seeking to understand how deep learning can be deployed for precise, automated quality assurance in high-stakes manufacturing environments.