Hsinchu, Taiwan

Chao-Jun Zhuang


Average Co-Inventor Count = 8.2

ph-index = 2

Forward Citations = 27(Granted Patents)


Company Filing History:


Years Active: 2012-2013

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2 patents (USPTO):Explore Patents

Title: Chao-Jun Zhuang: Innovator in 3D Image Database Technologies

Introduction

Chao-Jun Zhuang is a prominent inventor based in Hsinchu, Taiwan. He has made significant contributions to the field of 3D image database technologies. With a total of 2 patents, his work focuses on enhancing the understanding and management of complex data structures.

Latest Patents

Zhuang's latest patents include a "Method for searching and constructing 3D image database." This invention relates to methods for searching and constructing a 3D motif image database, which can be utilized to understand the connection relationships within a 3D network, such as biological or artificial neural networks. The methods applied to this database facilitate the management of vast amounts of categorized data while uncovering hidden information. Another notable patent is the "Image preprocessing system for 3D image database construction." This system includes a processing unit and an image preprocessing unit that preprocesses image slice data. It features an image fusion module to estimate missing values and an image stitching module to create stitched image data, all stored in a dedicated database.

Career Highlights

Chao-Jun Zhuang has worked with esteemed institutions such as Tsinghua University and National Applied Research Laboratories. His experience in these organizations has allowed him to develop innovative solutions in the realm of 3D imaging.

Collaborations

Zhuang has collaborated with notable colleagues, including Ann-Shyn Chiang and Ping-Chang Lee. Their joint efforts have contributed to advancements in their respective fields.

Conclusion

Chao-Jun Zhuang's work in 3D image database technologies showcases his innovative spirit and dedication to advancing the field. His patents reflect a commitment to improving data management and understanding complex networks.

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