Tokyo, Japan

Jingo Adachi



Average Co-Inventor Count = 1.3

ph-index = 1

Forward Citations = 7(Granted Patents)


Company Filing History:


Years Active: 2019-2024

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2 patents (USPTO):Explore Patents

Title: Jingo Adachi: Innovator in Information Estimation Technologies

Introduction

Jingo Adachi is a prominent inventor based in Tokyo, Japan. He has made significant contributions to the field of information estimation, particularly through his innovative patents. With a total of two patents to his name, Adachi's work focuses on enhancing the accuracy and efficiency of data analysis and environmental estimation.

Latest Patents

Adachi's latest patents include an "Information Estimation Apparatus and Information Estimation Method." This invention provides a technique for stable and fast computation of a variance representing a confidence interval for an estimation result. It utilizes a neural network that integrates a dropout layer and a fully connected layer to compute weights. The apparatus analyzes multivariate input data to determine the data type of each vector element in the output. Additionally, he has developed a "Surrounding Environment Estimation Device and Surrounding Environment Estimating Method." This technique improves the accuracy of environmental estimations using observation data from sensing equipment. It calculates a grid-unspecified logarithm-likelihood ratio and updates the occupation probability of detected objects in an occupancy grid map.

Career Highlights

Jingo Adachi is currently employed at Denso IT Laboratory, Inc., where he continues to innovate in the field of information technology. His work has been instrumental in advancing methods for data analysis and environmental sensing.

Collaborations

Adachi collaborates with Chiharu Yamano, contributing to the development of cutting-edge technologies in their field.

Conclusion

Jingo Adachi's contributions to information estimation technologies highlight his role as a leading inventor in Japan. His innovative patents reflect a commitment to enhancing data analysis and environmental estimation methods.

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