Hinohara-mura, Japan

Satoshi Watanabe

This inventor holds 1 USPTO granted patent. Top assignee: Evident Corporation. Active years: 2026.

IDiyas Innovation Intelligence. (2026). Inventor Profile: Satoshi Watanabe. Retrieved from https://idiyas.com/inventor/satoshi-watanabe-ta8lvdhy

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


Company Filing History:


Years Active: 2026

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1 patent (USPTO):Explore Patents

Title: Satoshi Watanabe and Neural-Network-Based Optical Data Processing.

Introduction

Satoshi Watanabe is an inventor associated with Hinohara-mura, Japan, and Evident Corporation. His patent work concerns using neural networks to estimate three-dimensional optical characteristics from measurements of light transmitted through an object.

Latest Patents

The supplied information lists one patent for Watanabe: “Data Processing Method and Learning Method.” The invention describes inputting measurement data into a trained neural network, generating estimated data, and restoring data through forward-propagation operations. It also calculates a confidence level for the estimate by comparing the measurement data with the restored data. The estimated three-dimensional optical characteristic is either a refractive-index distribution or an absorptance distribution. The method sequentially obtains estimated wavefronts as light travels through the object.

Career Highlights

Watanabe is associated with Evident Corporation. His listed patent applies neural-network processing to measurements of transmitted light, with the aim of estimating optical properties inside an object and assessing the confidence of those estimates.

Collaborations

The supplied information identifies Toshiro Okamura as Watanabe’s coworker. It does not specify whether they collaborated on the patent.

Conclusion

Satoshi Watanabe’s listed invention combines neural-network estimation and optical modeling to analyze an object’s internal characteristics, while also calculating confidence in the resulting estimates.

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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