Beijing, China

Qin Han


 

Average Co-Inventor Count = 6.4

ph-index = 1

Forward Citations = 4(Granted Patents)


Company Filing History:


Years Active: 2016-2025

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4 patents (USPTO):

Title: Innovations and Contributions of Inventor Qin Han

Introduction

Qin Han is a prominent inventor based in Beijing, China. He has made significant contributions to the fields of deep learning and image processing, particularly in the development of advanced methods for three-dimensional reconstruction and depth prediction.

Latest Patents

Qin Han holds four patents, showcasing his innovative approach to solving complex problems. His latest patents include a monocular video-based three-dimensional reconstruction and depth prediction method and system for pipelines. This invention relates to deep learning and image processing, utilizing the COLMAP method for feature extraction and matching. It constructs a three-dimensional reconstruction dataset and employs the Fast-MVSNet and PatchMatchNet networks for optimal results in actual pipeline scenes. Another notable patent is the ultra-high temperature resistant cement slurry system, which is designed for cementing in deep wells and ultra-deep wells at high temperatures. This system includes various components such as an ultra-high temperature strength stabilizer and a density regulator, demonstrating his expertise in material science.

Career Highlights

Qin Han has worked with notable companies, including Newish Technology (Beijing) Co., Ltd. and China National Petroleum Corporation. His experience in these organizations has allowed him to apply his innovative ideas in practical settings, contributing to advancements in technology and engineering.

Collaborations

Qin has collaborated with esteemed colleagues, including Chunhua Zhao and Jing Li. These partnerships have fostered a collaborative environment that encourages the exchange of ideas and enhances the quality of their work.

Conclusion

Qin Han's contributions to innovation and technology are evident through his patents and career achievements. His work continues to influence the fields of deep learning and material science, making a lasting impact on the industry.

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