The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Date of Patent:
Mar. 10, 2026

Filed:

Oct. 20, 2022
Applicant:

Mitsubishi Electric Research Laboratories, Inc., Cambridge, MA (US);

Inventors:

Pu Wang, Cambridge, MA (US);

Haifeng Xia, New Orleans, LA (US);

Toshiaki Koike Akino, Cambridge, MA (US);

Ye Wang, Cambridge, MA (US);

Philip Orlik, Cambridge, MA (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06N 3/094 (2023.01); G06F 18/213 (2023.01); G06F 18/214 (2023.01); G06F 18/25 (2023.01);
U.S. Cl.
CPC ...
G06N 3/094 (2023.01); G06F 18/213 (2023.01); G06F 18/2155 (2023.01); G06F 18/25 (2023.01);
Abstract

The present disclosure provides a method and a system for training a neural network suitable for localization of a device within an environment based on signals received by the device. The method comprises training a bi-regressor neural network to identify locations from labeled data, wherein the bi-regressor neural network includes a feature extractor and a bi-regressor including two regressors; training parameters of the bi-regressor using the labeled data and unlabeled data, such that each of the two regressors identifies the same labeled locations while processing the labeled data and identifies different locations while processing the unlabeled data; and training parameters of the feature extractor using an adversarial discriminator to extract domain invariant features from the unlabeled data with statistical properties of the labeled data according to the adversarial discriminator such that each of the two regressors identifies the same locations while processing the domain invariant features.


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