Hefei, China

Haitao Wang


Average Co-Inventor Count = 6.5

ph-index = 1


Company Filing History:


Years Active: 2023-2024

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3 patents (USPTO):Explore Patents

Title: Innovations of Haitao Wang in Driver Distraction Detection

Introduction

Haitao Wang is a prominent inventor based in Hefei, China, known for his contributions to the field of driving behavior analysis. He has been instrumental in developing innovative methods for detecting driver distraction, which is crucial for enhancing road safety.

Latest Patents

Haitao Wang holds three patents, with his latest innovations focusing on advanced detection methods for driver distraction. One of his notable patents is 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 the data and determine the driver's distraction state. The model incorporates a RepMLP network structure and employs a loss function based on contrastive learning.

Another significant patent is the "Transformer-based driver distraction detection method and apparatus." This innovation includes building a driver distraction detection model, referred to as FPT, which analyzes distracted driving image data to determine the distraction state. The FPT model improves classification accuracy while reducing the parameter quantity and calculation amount compared to traditional deep learning models.

Career Highlights

Haitao Wang is affiliated with Anhui University, where he continues to advance research in driving behavior analysis. His work has garnered attention for its practical applications in improving road safety through technology.

Collaborations

Haitao Wang collaborates with notable colleagues, including Jie Chen and Bing Li, who contribute to his research endeavors and innovations in the field.

Conclusion

Haitao Wang's innovative patents and research in driver distraction detection represent significant advancements in the field of driving behavior analysis. His work not only enhances understanding of driver distraction but also contributes to the development of safer driving technologies.

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