Prof Sam Kwong Tak-wu receives the Natural Science Award (First Prize) at the Shandong Computer Federation Science and Technology Awards. (From left: Prof Sam Kwong Tak-wu, Prof Cong Runmin)
The project addresses three major scientific challenges currently facing drones, and significantly reinforces their operational capabilities in complex scenarios. In recognition of their outstanding contributions to drone technology research, application, and innovation, the team was awarded the Natural Science Award (First Prize), the highest honour of the 2025 Shandong Computer Federation Science and Technology Awards.
Supported by the National Natural Science Foundation of China, the research focuses on three key challenges faced by drones in complex environments, including “unstable imagery”, “difficulty in identifying targets within complex backgrounds”, and “achieving sustaining technological enhancements at low cost”, and has made three key scientific breakthroughs. First, the team explored how to improve drone visual capabilities in specific scenarios, enabling the systems to adapt quickly to different environments and obtain clearer, more stable critical information even under adverse conditions. Second, the team established a multi-layered analysis approach that allows drones to identify specific targets within complex backgrounds. Finally, they achieved sustainable and cost-effective development and improvement of drone systems.
Technologies derived from this research have already been commercialised and adopted by AI companies such as State Grid Intelligence Technology and Shandong Boyuan Video Information Technology, and greatly strengthen the autonomous perception and decision-making capabilities of drones in multiple situations, including traffic management, emergency response, vegetation protection, and power facility inspection patrols so that drones can overcome more environmental constraints, and complete tasks better and more efficiently.
Prof Kwong said “I am deeply honoured to receive this award. It is not only a recognition of my personal achievements, but also an acknowledgment of the collective research of the entire team, which aims to overcome the developmental challenges drones face in complex environments, and not only advances drone technology but also contributes to human well-being, opening up broader application prospects and potential in areas concerning human welfare such as rescue operations and environmental protection. We shall continue to research and use innovative technologies, thus enabling society to benefit from technological transformation.”
Five representative papers from the project have been published in top international journals and at academic conferences, including IEEE Transactions on Pattern Analysis and Machine Intelligence; The International Journal of Computer Vision; Computer Vision and Pattern Recognition; IEEE Transactions on Multimedia; and ACM Multimedia, and acquired 2,572 Google Scholar citations. One is a Highly Cited Paper in the Essential Science Indicators Database, and another has received over 2,000 Google Scholar citations. The research has received widespread recognition and positive evaluations from experts in the field, including the Chinese Academy of Engineering; The Academy of Engineering Singapore (SAEng); Foreign Members of the Academia Europaea, and IEEE Fellows.
The project was carried out by Prof Sam Kwong Tak-wu; Prof Cong Runmin from the School of Control Science and Engineering of Shandong University; Prof Guo Chunle, Associate Professor of the College of Computer Science at Nankai University; Prof Li Feng from the School of Computer Science and Technology at the Hefei University of Technology; Prof Bai Huihui from the Institute of Information Sciences at Beijing Jiaotong University; and Prof Zhang Wei from the School of Control Science and Engineering of Shandong University.
