Yingjian Deng

Title: Innovations by Yingjian Deng in Driver Distraction Detection

Introduction

Yingjian Deng is an accomplished inventor based in Hefei, China. He has made significant contributions to the field of driving behavior analysis, particularly in the area of driver distraction detection. With a total of 2 patents, his work focuses on enhancing safety in driving through innovative methods.

Latest Patents

Yingjian Deng's latest patents include a "Method for fine-grained detection of driver distraction based on unsupervised learning." This method involves acquiring distracted driving image data and utilizing an unsupervised learning detection model to analyze this data. The model incorporates a backbone network, projection heads, and a loss function, which collectively determine the driver's distraction state based on the analysis results.

Another notable patent is the "Transformer-based driver distraction detection method and apparatus." This invention also focuses on analyzing distracted driving image data through a newly proposed driver distraction detection model, FPT. The FPT model improves classification accuracy while reducing the parameter quantity and calculation amount compared to traditional deep learning models. It also adjusts the loss function to enhance classification accuracy and suppress overfitting.

Career Highlights

Yingjian Deng is affiliated with Anhui University, where he continues to advance research in driving behavior analysis. His innovative approaches have positioned him as a key figure in the development of technologies aimed at improving road safety.

Collaborations

Yingjian has collaborated with notable colleagues such as Jie Chen and Haitao Wang, contributing to the advancement of research in his field.

Conclusion

Yingjian Deng's contributions to driver distraction detection through his innovative patents reflect his commitment to enhancing road safety. His work continues to influence the field of driving behavior analysis significantly.