公开(公告)号：US12111189B2

公开(公告)日：2024-10-08

申请号：US17221822

申请日：2021-04-04

Applicant: NEC Laboratories America, Inc.

Inventor： Ming-Fang Huang ,  Ting Wang ,  Shaobo Han

IPC: G01D5/353 ,  G01H9/00 ,  G06V20/58 ,  G08B21/18

CPC classification number: G01D5/353 ,  G01D5/35361 ,  G01D5/35364 ,  G01H9/004 ,  G06V20/58 ,  G08B21/18

Abstract: Aspects of the present disclosure describe distributed fiber optic sensing (DFOS) systems, methods, and structures that advantageously identify location(s) of construction—or other activities—taking place along fiber optic cable routes that can damage the fiber optic cables.

公开(公告)号：US20240087196A1

公开(公告)日：2024-03-14

申请号：US18463784

申请日：2023-09-08

Applicant: NEC Laboratories America, Inc.

Inventor： Renqiang Min ,  Kai Li ,  Shaobo Han ,  Hans Peter Graf ,  Changhao Shi

IPC: G06T11/60 ,  G06T9/00 ,  G06V10/764 ,  G06V10/774

CPC classification number: G06T11/60 ,  G06T9/002 ,  G06V10/764 ,  G06V10/774

Abstract: Methods and systems for image generation include generating a latent representation of an image, modifying the latent representation of the image based on a trained attribute classifier and a specified attribute input, and decoding the modified latent representation to generate an output image that matches the specified attribute input.

公开(公告)号：US11698290B2

公开(公告)日：2023-07-11

申请号：US17714091

申请日：2022-04-05

Applicant: NEC Laboratories America, Inc.

Inventor： Shaobo Han ,  Yue Tian ,  Sarper Ozharar ,  Yangmin Ding ,  Ting Wang

IPC: G01H9/00

CPC classification number: G01H9/004

Abstract: Systems and methods for operating a distributed fiber optic sensing (DFOS)/distributed acoustic sensing (DAS) system include a length of optical sensing fiber suspended aerially by a plurality of utility poles and in optical communication with a DFOS interrogator/analyzer. The method includes operating the DFOS/DAS system while manually exciting more than one of the poles to obtain frequency response(s) of the excited poles; contrastively training a convolutional neural network (CNN) with the frequency responses obtained; classifying the utility poles using the contrastively trained CNN; and generating a profile map of the excited poles indicative of the classified utility poles.