Dr. Zekun Li – Leading Researcher in Graphic analysis
Dr. Zekun Li a distinguished academic and researcher in the field of Graphic analysis,His academic journey began with a Bachelor of Science degree in Optoelectronic Information Science and Engineering (OSE) at Xi’an University of Posts and Telecommunications (XUPT), Shaanxi, China, where he completed his undergraduate studies from 2014 to 2018. 📚
Education📚
Research interests
- Fast 2D Shape Recognition, Fast 3D Shape Recognition, Deep
Learning, Constrain Reduction of Feature Structure
Honors and awards
He has demonstrated exceptional academic and innovative achievements throughout his educational journey. Achieving the First Prize in ‘The Second National College Internet of Things Technology and Application ‘Three Creation’ Competition’ highlights his prowess in IoT technology. As an Excellent Student at Xi’an University of Posts and Telecommunications, he received recognition for his outstanding performance. Winning the First Prize in the 14th China Postgraduate Electronic Design Contest for the Northwest Region further underscores his excellence in electronic design. Additionally, his contribution to the development of a Rugged Terrain Measurement System based on Beidou earned him the Third Prize in the Postgraduate Group. Acknowledged as an Outstanding Graduate Student at Xidian University, he has consistently received academic scholarships every year since 2014, showcasing his sustained commitment to scholarly excellence. 🏆🎓
Patent
• Baolong Guo, Li, Zekun, Wenqiang Mo, et al., A shape description and retrieval
method based on the vertical inner-distance ratio of minimum bounding rectangle
(Publicly available)
• Baolong Guo, Li, Zekun, Chao Wang, et al., An intelligent scene perception
defense device and method based on multi-source information fusion (Publicly
available)
• Chao Wang, Baolong Guo, Li, Zekun, et al., A frequency domain sparse signal
transmission and reception system implementation method based on IFFT (Publicly available)
• Chao Wang, Baolong Guo, Li, Zekun, et al., A garbage image classification
method based on transfer learning (Publicly available)
Published
- Li, Zekun, Baolong Guo, and Fanjie Meng. ”Fast Shape Recognition Method
Using Feature Richness Based on the Walking Minimum Bounding Rectangle
over an Occluded Remote Sensing Target.” Remote Sensing 14.22 (2022): 5845
- Li, Zekun, Baolong Guo, and Cheng Li. ”Interior Distance Ratio to a Regular
Shape for Fast Shape Recognition.” Symmetry 14.10 (2022): 2040
- ”Fast Shape Recognition via the Restraint Reduction of Bone Point Segmenthttps://doi.org/10.3390/sym14081670.” Symmetry 14.8 (2022): 1670
- A Fourier Descriptor for Bone Point Segmentation using inner distance in remote sensing images.” 2022
IEEE 46th Annual Computers, Software, and Applications Conference (COMPSAC). IEEE, 2022
- ”A multi-angle shape descriptor with the distance ratio to vertical bounding rectangles.” 2021 International Conference on Content-Based Multimedia Indexing (CBMI). IEEE, 2021
- Vertical Interior Distance Ratio to Minimum Bounding Rectangle of a Shape.” Hybrid Intelligent Systems:
20th International Conference on Hybrid Intelligent Systems (HIS 2020), December 14-16, 2020. Springer International Publishing, 2021