公开(公告)号：US20250148281A1

公开(公告)日：2025-05-08

申请号：US18909467

申请日：2024-10-08

Applicant: NEC Laboratories America, Inc.

Inventor： Shaobo Han ,  Tingfeng Li ,  Renqiang Min

IPC: G06N3/08

Abstract: Systems and methods include collecting real-world distributed-optic fiber sensing (DFOS) sensing data from a target environment as a reference dataset. A synthetic sketch dataset is constructed as a parameterized computer program. A synthetic waterfall is generated from a deep neural network as an image translator from the sketch waterfall with nonlinear distortions and background noises added. Parameters are optimized for generating the synthetic waterfall under a loss function where the loss function encodes a generalization performance on the real-world dataset and encodes granularities from a sensing process and uncontrollable factors.

公开(公告)号：US12038320B2

公开(公告)日：2024-07-16

申请号：US17556928

申请日：2021-12-20

Applicant: NEC Laboratories America, Inc.

Inventor： Shaobo Han ,  Yuheng Chen ,  Ming-Fang Huang ,  Tingfeng Li

IPC: G01H9/00 ,  B60W30/18 ,  G06V10/14 ,  G06V10/82 ,  G06V20/52 ,  H04B10/2537

CPC classification number: G01H9/004 ,  B60W30/18 ,  G06V10/14 ,  G06V10/82 ,  G06V20/52 ,  H04B10/2537 ,  B60W2420/406 ,  G06V2201/08

Abstract: A fiber optic sensing technology for vehicle run-off-road incident automatic detection by an indicator of sonic alert pattern (SNAP) vibration patterns. A machine learning method is employed and trained and evaluated against a variety of heterogeneous factors using controlled experiments, demonstrating applicability for future field deployment. Extracted events resulting from operation of our system may be advantageously incorporated into existing management systems for intelligent transportation and smart city applications, facilitating real-time alleviation of traffic congestion and/or providing a quick response rescue and clearance operation.

公开(公告)号：US20230130788A1

公开(公告)日：2023-04-27

申请号：US17958415

申请日：2022-10-02

Applicant: NEC Laboratories America, Inc.

Inventor： Sarper OZHARAR ,  Ting WANG ,  Yue TIAN ,  Yangmin DING ,  Philip JI ,  Shaobo Han ,  Ming-Fang Huang ,  Tingfeng Li

IPC: G01H9/00 ,  G01D5/353 ,  H04B10/071

Abstract: Aspects of the present disclosure describe distributed fiber optic sensing (DFOS) systems, methods, and structures that advantageously sense/monitor outdoor facilities and structures including outdoor cabinets containing fiber optic facilities in which the cabinet/fiber optic cable contained therein are configured to provide superior acoustic sensing. Further outdoor facilities and structures that are monitored include manhole structures. Superior DFOS/DAS monitoring results are obtained by employing a machine learning-based analysis method that employs a temporal relation network (TRN).

公开(公告)号：US12205357B2

公开(公告)日：2025-01-21

申请号：US17715901

申请日：2022-04-07

Applicant: NEC Laboratories America, Inc.

Inventor： Shaobo Han ,  Renqiang Min ,  Tingfeng Li

IPC: G06V10/778 ,  G06V10/82 ,  G06V30/19

Abstract: A reinforcement learning based approach to the problem of query object localization, where an agent is trained to localize objects of interest specified by a small exemplary set. We learn a transferable reward signal formulated using the exemplary set by ordinal metric learning. It enables test-time policy adaptation to new environments where the reward signals are not readily available, and thus outperforms fine-tuning approaches that are limited to annotated images. In addition, the transferable reward allows repurposing of the trained agent for new tasks, such as annotation refinement, or selective localization from multiple common objects across a set of images. Experiments on corrupted MNIST dataset and CU-Birds dataset demonstrate the effectiveness of our approach.