Beijing, China

Guodong Ni

USPTO Granted Patents = 1 

Average Co-Inventor Count = 6.0

ph-index = 1


Company Filing History:


Years Active: 2025

where 'Filed Patents' based on already Granted Patents

1 patent (USPTO):

Title: Guodong Ni: Innovator in Crowd Counting Technology

Introduction

Guodong Ni is a prominent inventor based in Beijing, China. He has made significant contributions to the field of crowd counting systems through his innovative methods. His work focuses on enhancing the accuracy of crowd density mapping, which is crucial for various applications in public safety and event management.

Latest Patents

Guodong Ni holds a patent for a method titled "Method for generating training data on basis of deformable Gaussian kernel in population counting system." This patent discloses a systematic approach to generating training data using deformable Gaussian kernels. The method involves several steps, including finding overlapping Gaussian kernels, stretching and rotating occluded kernels, and adjusting their center point coordinates. The result is a crowd density map that significantly improves feature similarity with actual images, thereby enhancing the learning process of convolutional neural networks and increasing the accuracy of crowd counting systems.

Career Highlights

Guodong Ni is associated with Crsc Communication & Information Group Company Ltd., where he applies his expertise in developing advanced technologies for crowd counting. His innovative approach has positioned him as a key figure in the field, contributing to the company's reputation for excellence in communication and information solutions.

Collaborations

Guodong Ni collaborates with notable colleagues such as Yang Liu and Weiming Hu. Their combined efforts in research and development have led to advancements in crowd counting technologies and methodologies.

Conclusion

Guodong Ni's contributions to the field of crowd counting through his innovative patent demonstrate his commitment to improving technology in this area. His work not only enhances the accuracy of crowd density mapping but also showcases the potential for future advancements in public safety applications.

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