Masataka Sugiura

Title: Masataka Sugiura: Innovator in Learned Model Technologies

Introduction

Masataka Sugiura, based in Tokyo, Japan, is a prolific inventor with an impressive portfolio of 25 patents. His work primarily focuses on advancements in learned model generating technologies, contributing significantly to the fields of machine learning and data utilization.

Latest Patents

Among Sugiura's latest inventions are three notable patents: a learned model generating method, a learned model generating device, and a learned model use device. These innovations comprise a learned model providing system which includes several key components. It features a consent acquisition device that obtains consent for the use of visitor images for generating learned models. The system integrates multiple cameras for imaging visitors, and a learned model generating device that utilizes machine learning to create these models based on captured images. Additionally, a server device is employed to store the generated learned model, which is then accessible to a user side device. Sugiura's inventions also entail a method for selecting learned models corresponding to sensing data and a learned model provision device that selectively provides the learned model based on user needs.

Career Highlights

Sugiura has made significant contributions during his tenure at renowned companies, including Matsushita Electric Industrial Co., Ltd. and Panasonic Corporation. His roles at these organizations have allowed him to pioneer innovations that bridge technology and practical applications.

Collaborations

Throughout his career, Sugiura has collaborated with esteemed colleagues such as Mikio Morioka and Toru Kubo. These partnerships have fostered an environment of shared knowledge and innovative brainstorming, contributing to the advancement of the technologies for which he is known.

Conclusion

Masataka Sugiura stands out as a leading figure in the realm of learned model technologies. His dedication to innovation and development continues to drive forward the capabilities of machine learning systems, paving the way for future technological advancements.