公开(公告)号：US20230315783A1

公开(公告)日：2023-10-05

申请号：US18176841

申请日：2023-03-01

Applicant: NEC Corporation

Inventor： Asako FUJII ,  Iain MELVIN ,  Yuki CHIBA ,  Masayuki SAKATA ,  Erik KRUUS ,  Chris WHITE

IPC: G06F16/583 ,  G06F16/55 ,  G06F16/58

CPC classification number: G06F16/583 ,  G06F16/55 ,  G06F16/5866

Abstract: A classification apparatus according to the present disclosure includes an input unit configured to receive an operation performed by a user, an extraction unit configured to extract moving image data by using a predetermined rule, a display control unit configured to display an icon corresponding to the extracted moving image data on a screen of a display unit, a movement detection unit configured to detect a movement of the icon on the screen caused by the operation performed by the user, and a specifying unit configured to specify a classification of the moving image data corresponding to the icon based on a position of the icon on the screen.

公开(公告)号：US20240085196A1

公开(公告)日：2024-03-14

申请号：US18274909

申请日：2021-02-01

Applicant: NEC Corporation

Inventor： Asako FUJII ,  Takuroh KASHIMA

IPC: G01C21/34 ,  G06N3/092

CPC classification number: G01C21/3446 ,  G01C21/343 ,  G01C21/3453 ,  G06N3/092

Abstract: A function input means 71 accepts input of a cost function that calculates a cost incurred by an itinerary, the cost function being expressed as a linear sum of terms weighted for each feature that a traveler is expected to intend in the itinerary. A learning means 72 learns the cost function by inverse reinforcement learning using training data that includes scheduled information indicating travel planning of the traveler, attribute information indicating an attribute of the traveler, and actual information indicating an actual travel result of the traveler. A data extraction means 73 extracts the training data whose specified attribute matches the attribute information. Then, the learning means 72 learns the cost function according to the attributes by inverse reinforcement learning using the extracted training data.

公开(公告)号：US20250037476A1

公开(公告)日：2025-01-30

申请号：US18841479

申请日：2022-03-11

Applicant: NEC Corporation

Inventor： Masayuki SAKATA ,  Asako FUJII

IPC: G06V20/58 ,  G06T7/20 ,  G06T7/70 ,  G06V20/70

Abstract: Provided is an information processing apparatus (10) including: a specification means (11) for specifying, from a period within a video captured by an image capturing apparatus installed in a vehicle, a period in which information being recognized from a video matches with a rule according to a specific scene; an acquisition means (12) for acquiring a data set being a combination of information being recognized from a video in the period specified by the specification means and a correct label indicating whether the video in the period is a video of the specific scene; and a generation means (13) for executing learning, based on the data set acquired by the acquisition means, and generating a trained model for estimating whether a video in a specific period is a video of the specific scene.

公开(公告)号：US20220274608A1

公开(公告)日：2022-09-01

申请号：US17627969

申请日：2020-05-22

Applicant: NEC Corporation

Inventor： Asako FUJII ,  Yusuke KOITABASHI ,  Takuroh KASHIMA ,  Yuki CHIBA ,  Kenji SOBATA

IPC: B60W50/00 ,  B60W40/08 ,  G06N20/00

Abstract: A comfort determination model learning unit 81 learns a comfort determination model, by using comfortable activity data where a comfort indicator, which is an indicator measuring whether an individual is comfortable or not when an activity classified as a comfortable activity is performed, is associated with a teacher label indicating comfort, and uncomfortable activity data where the comfort indicator when an activity classified as an uncomfortable activity is performed, is associated with a teacher label indicating discomfort, as first training data, taking an objective variable for a comfort value indicating a degree of comfort, and taking an explanatory variable for each of the comfort indicators. An individual data generation unit 82 generates individual data including explanatory variables, which are used in the comfort determination model, generated based on the comfort indicators of the subject during riding on a vehicle, and driving situations of the vehicle when the comfort indicators are obtained. A driving data generation unit 83 generates comfortable driving data and uncomfortable driving data according to a comfort value calculated by applying the individual data to the comfort determination model.