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.

公开(公告)号：US20210390283A1

公开(公告)日：2021-12-16

申请号：US17288607

申请日：2019-09-17

Applicant: NEC Corporation

Inventor： Yasunori FUTATSUGI ,  Yoshihiro MISHIMA ,  Atsushi FUKUZATO ,  Jun NAKAYAMADA ,  Kenji SOBATA

IPC: G06K9/00 ,  G06K9/62

Abstract: An object recognition system 80 includes: a recognition device 30 that recognizes an object in an image; and a server 40 that generates a learning model. The recognition device 30 includes: a first object recognition unit 310 that determines a type of the object in the image using the learning model; and an image transmission unit 320 that transmits a type-indeterminable image, which is an image in which the type has not been determined, to the server 40 when an object included in the type-indeterminable image is an object detected as a three-dimensional object. The server 40 includes: a learning device 410 that generates the learning model based on training data in which a teacher label is assigned to the type-indeterminable image; and a learning model transmission unit 420 that transmits the generated learning model to the recognition device 30. The first object recognition unit 310 determines the type of the object in the image using the transmitted learning model.

公开(公告)号：US20230092026A1

公开(公告)日：2023-03-23

申请号：US17801463

申请日：2020-03-19

Applicant: NEC Corporation

Inventor： Noritaka YAMASHITA ,  Kenji SOBATA ,  Masayuki SAKATA ,  Yuki CHIBA

IPC: G07C5/02

Abstract: The present invention provides a processing apparatus (10) including: a determination unit (12) determining a predetermined vehicle state and a predetermined ambient environment, based on user vehicle data indicating a vehicle state and an ambient environment when a user uses a vehicle; a computation unit (13) computing a degree of similarity between the predetermined vehicle state and the predetermined ambient environment, and a vehicle state and an ambient environment indicated by a vehicle running test scenario; and an output unit (14) outputting a computation result by the computation unit (13).

公开(公告)号：US20220001858A1

公开(公告)日：2022-01-06

申请号：US17293564

申请日：2019-09-13

Applicant: NEC Corporation

Inventor： Yasunori FUTATSUGI ,  Yoshihiro MISHIMA ,  Atsushi FUKUZATO ,  Jun NAKAYAMADA ,  Kenji SOBATA ,  Yuki CHIBA

IPC: B60W30/08 ,  G06K9/00 ,  G06N3/08

Abstract: A dangerous scene prediction device 80 for predicting a dangerous scene occurring during driving of a vehicle includes a learning model selection/synthesis unit 81 and a dangerous scene prediction unit 82. The learning model selection/synthesis unit 81 selects, from two or more learning models, a learning model used for predicting the dangerous scene, depending on a scene determined based on information obtained during the driving of the vehicle. The dangerous scene prediction unit 82 predicts the dangerous scene occurring during the driving of the vehicle, using the selected learning model.

公开(公告)号：US20210390353A1

公开(公告)日：2021-12-16

申请号：US17287182

申请日：2019-09-13

Applicant: NEC Corporation

Inventor： Yasunori FUTATSUGI ,  Yoshihiro MISHIMA ,  Atsushi FUKUZATO ,  Jun NAKAYAMADA ,  Kenji SOBATA

IPC: G06K9/62 ,  G06K9/00

Abstract: An object recognition device 80 includes a scene determination unit 81, a learning-model selection unit 82, and an object recognition unit 83. The scene determination unit 81 determines, based on information obtained during driving of a vehicle, a scene of the vehicle. The learning-model selection unit 82 selects, in accordance with the determined scene, a learning model to be used for object recognition from two or more learning models. The object recognition unit 83 recognizes, using the selected learning model, an object in an image to be photographed during driving of the vehicle.