Ms Xianhui Zong | Transportation Award | Best Researcher Award
Ms Xianhui Zong, Nanjing University of Science and Technology ,China
Xianhui Zong, a dedicated Ph.D. candidate at Nanjing University of Science and Technology, has a solid academic foundation with a B.S. and M.S. in Mechanical Engineering from the University of Science and Technology Beijing. Her research interests lie in deep learning, computer vision, and intelligent transport. Xianhui has contributed significantly to her field, with four journal publications and an ongoing patent. Her work focuses on advancing intelligent monitoring and control of road risks, aiming to enhance transportation safety and efficiency 🚀📚.
Publication Profile
Scopus
Education
Xianhui Zong is a dedicated researcher pursuing her Ph.D. at the School of Intellectual Property, Nanjing University of Science and Technology. She holds a B.S. and M.S. in Mechanical Engineering from the University of Science and Technology Beijing, obtained in 2018 and 2021, respectively. Her research focuses on deep learning, computer vision, and intelligent transport 🚗💡. With a solid academic background and a passion for technological advancements, Xianhui aims to contribute significantly to the field of intelligent transport systems, enhancing safety and efficiency on the roads through innovative solutions and cutting-edge research 📚🔍.
Research Focus
Xianhui Zong’s research primarily focuses on artificial intelligence and computer science, specifically within the realms of deep learning, computer vision, and intelligent transport 🚗💡. She aims to advance technological innovations for real-time high-precision pedestrian tracking, visual enhancement in complex environments, and temperature field analysis during manufacturing processes. Her work seeks to enhance safety and efficiency in transportation and industrial applications through cutting-edge AI solutions and intelligent monitoring systems 📚🔍. Xianhui’s research contributions are pivotal in developing smarter, more efficient systems that can adapt to dynamic real-world conditions 🌐🔧.
Publication Top Notes
Real-time high-precision pedestrian tracking: a detection–tracking–correction strategy based on improved SSD and Cascade R-CNN (2022) – 11 citations 📄🔍
Local-CycleGAN: a general end-to-end network for visual enhancement in complex deep-water environment (2021) – 24 citations 🌊📈
Analysis of the temperature field during the selective laser melting process based on a finite element model (2019) – 2 citations 🔥🖥️
Online monitoring based on temperature field features and prediction model for selective laser sintering process (2018) – 14 citations 🌡️📊
Image processing methods based on key temperature features for state analysis and process monitoring of selective laser melting (SLM) (2018) – 2 citations 📸📉