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NEC Corporation Multi-Sensor Encoding and Adversarial Estimation Machine Learning Device Patent Application

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Summary

USPTO published patent application US20260099724A1 for NEC Corporation's machine learning device that trains encoding models for sensor data and adversarial estimation models. The invention encodes first and second sensor data into codes, trains an adversarial estimation model to estimate cross-modal codes, and trains the encoding model to resist adversarial estimation. This publication affects technology companies and manufacturers developing multi-sensor machine learning systems.

Published by USPTO on changeflow.com . Detected, standardized, and enriched by GovPing. Review our methodology and editorial standards .

What changed

USPTO published patent application US20260099724A1 for NEC Corporation's machine learning device that trains encoding models for first and second sensor data and trains an adversarial estimation model to estimate cross-modal codes. The system trains the encoding model to resist adversarial estimation, creating a robust cross-modal estimation framework.

Technology companies and manufacturers developing multi-sensor machine learning systems should monitor this application for potential licensing implications or freedom-to-operate concerns. Inventors and patent applicants may also reference this application as prior art when evaluating similar machine learning architectures.

What to do next

  1. Monitor for patent grant or examination updates
  2. Review for potential licensing or freedom-to-operate implications

Archived snapshot

Apr 15, 2026

GovPing captured this document from the original source. If the source has since changed or been removed, this is the text as it existed at that time.

← USPTO Patent Applications

MACHINE LEARNING DEVICE, ESTIMATION SYSTEM, TRAINING METHOD, AND RECORDING MEDIUM

Application US20260099724A1 Kind: A1 Apr 09, 2026

Assignee

NEC Corporation

Inventors

Kenichiro FUKUSHI, Hiroshi KAJITANI, Fumiyuki NIHEY, Chenhui HUANG, Kazuki IHARA, Zhenwei WANG, Yoshitaka NOZAKI, Kentaro NAKAHARA

Abstract

A machine learning device that trains a first encoding model for encoding first sensor data into first code, a second encoding model for encoding second sensor data into second code, and an estimation model for making estimation using the first code and the second code such that an estimation result from the estimation model conforms to correct answer data, trains a first adversarial estimation model that outputs an estimated value of the second code in response to the input of the first code such that the estimated value of the second code estimated by the first adversarial estimation model conforms to the second code outputted from the second encoding model, and trains the first encoding model such that the estimated value of the second code estimated by the first adversarial estimation model does not conform to the second code outputted from the second encoding model.

CPC Classifications

G06N 3/094 G06N 3/045

Filing Date

2025-12-10

Application No.

19414754

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Last updated

Classification

Agency
USPTO
Published
April 9th, 2026
Instrument
Notice
Legal weight
Non-binding
Stage
Final
Change scope
Minor
Document ID
US20260099724A1

Who this affects

Applies to
Technology companies Manufacturers
Industry sector
5112 Software & Technology
Activity scope
Machine learning system development Patent application filing Multi-sensor system design
Geographic scope
United States US

Taxonomy

Primary area
Intellectual Property
Operational domain
Legal
Topics
Artificial Intelligence Data Privacy

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