Taipei, Taiwan

Shr-Tze Wan

This inventor holds 2 USPTO granted patents and 1 published patent application. Top assignee: Kneron (Taiwan) Co., Ltd.. Active years: 2026.

IDiyas Innovation Intelligence. (2026). Inventor Profile: Shr-Tze Wan. Retrieved from https://idiyas.com/inventor/shr-tze-wan

Data source: USPTO (United States Patent and Trademark Office) public patent records. Weekly synchronization. How IDiyas builds this profile

Calculating rank
USPTO Granted Patents = 2 

Average Co-Inventor Count = 5.0

ph-index = 1


Company Filing History:


Years Active: 2026

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2 patents (USPTO):Explore Patents

Title: Shr-Tze Wan and Multi-Camera People Matching

Introduction

Shr-Tze Wan is an inventor based in Taipei, Taiwan, associated with Kneron (Taiwan) Co., Ltd. His patent work addresses computer vision and the use of machine learning to match and select people across multiple camera views.

Latest Patents

Wan is named on 1 patent: “Multi-camera people matching and selection method.” The invention captures images from multiple cameras and uses a machine-learning model to generate member features. It synchronizes those features with corresponding images, then identifies people by comparing feature embeddings and considering spatial relationships detected from objects or audio direction. The method also adjusts preference and display scores to select images that present people smoothly and favor those who are present.

Career Highlights

Wan’s listed patent reflects work on combining multi-camera imagery, machine-learning features, and matching techniques for people identification and image selection. His professional association with Kneron (Taiwan) Co., Ltd. connects this work to the company’s technology activities.

Collaborations

Wan’s listed coworkers include Hsien-Kai Hsin and Chih-Yu Wang.

Conclusion

Shr-Tze Wan’s patent describes a coordinated approach to matching people across camera feeds and selecting suitable images, highlighting his contribution to machine-learning-based vision technology.

Profile summary based on public USPTO records.
Data Sources: USPTO Patent Grant XML, Patent Center, EPO & CIPO • Normalized by IDiyas Innovation Graph. Methodology & provenance architecturePlease report any incorrect information to [email protected]
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