Suwon, South Korea

Sanggul Park

This inventor holds 1 USPTO granted patent. Top assignee: Samsung Electronics Ltd.. Active years: 2026.

IDiyas Innovation Intelligence. (2026). Inventor Profile: Sanggul Park. Retrieved from https://idiyas.com/inventor/sanggul-park

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


Average Co-Inventor Count = 1.0

ph-index = 1


Company Filing History:


Years Active: 2026

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1 patent (USPTO):Explore Patents

Title: Sanggul Park - Innovator in Neural Network Technology

Introduction

Sanggul Park is an inventor based in Suwon-si, South Korea. He has made significant contributions to the field of neural networks, particularly through his innovative patent application. His work focuses on enhancing the capabilities of neural network devices and systems.

Latest Patent Applications

Sanggul Park's notable patent application is titled "NEURAL NETWORK DEVICE AND SYSTEM AND OPERATING METHOD OF THE NEURAL NETWORK DEVICE." This application describes a neural network device that includes a pre-processor for selecting target images from scanning electron microscope (SEM) images. The pre-processor is designed to crop these images into multiple cropped images based on their respective frequencies. Additionally, a neural network processor is utilized to generate a crop detection image by inferring target objects from the cropped images using a trained segmentation model. Finally, a post-processor merges the crop detection images into a size that matches the original SEM images, based on the position information of the cropped images.

Conclusion

Sanggul Park's innovative approach to neural network technology showcases his potential as an inventor in this rapidly evolving field. His contributions may pave the way for advancements in image processing and analysis.

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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