公开(公告)号：US20230162093A1

公开(公告)日：2023-05-25

申请号：US18147671

申请日：2022-12-28

Applicant: DASSAULT SYSTEMES

Inventor： Louis DUPONT DE DINECHIN

IPC: G06N20/00 ,  G06F16/22

CPC classification number: G06N20/00 ,  G06F16/22 ,  G06F30/10

Abstract: The disclosure notably relates to a computer-implemented method for teaching a generative autoencoder. The generative autoencoder is configured to generate functional structures. A functional structure is a data structure representing a mechanical assembly of rigid parts and which includes a tree. Each leaf node represents a shape and positioning of a respective rigid part and a force exerted on the respective rigid part. Each non-leaf node with several children represents a mechanical link between sub-assemblies. Each sub-assembly is represented by a respective one of the several children. Each non-leaf node with a single child represents a duplication of the sub-assembly represented by the single child. The method includes obtaining a dataset including functional structures. The method further comprises teaching the generative autoencoder on the dataset. This constitutes an improved method for teaching a generative autoencoder configured for generating functional structures.

公开(公告)号：US20180322371A1

公开(公告)日：2018-11-08

申请号：US15973165

申请日：2018-05-07

Applicant: DASSAULT SYSTEMES

Inventor： Louis DUPONT DE DINECHIN ,  Asma REJEB SFAR

IPC: G06K9/62 ,  G06N3/08

CPC classification number: G06K9/6259 ,  G06K9/3216 ,  G06K9/4628

Abstract: A computer-implemented method of signal processing comprises providing images. The method comprises for each respective one of at least a subset of the images: applying a weakly-supervised learnt function, the weakly-supervised learnt function outputting respective couples each including a respective localization and one or more respective confidence scores, each confidence score representing a probability of instantiation of a respective object category at the respective localization. The method further comprises determining, based on the output of the weakly-supervised learnt function, one or more respective annotations, each annotation including a respective localization and a respective label representing instantiation a respective object category at the respective localization. The method further comprises forming a dataset including pieces of data, each piece of data including a respective image of the subset and at least a part of the one or more annotations determined for the respective image. This improves the field of object detection.

公开(公告)号：US20210004719A1

公开(公告)日：2021-01-07

申请号：US16922911

申请日：2020-07-07

Applicant: DASSAULT SYSTEMES

Inventor： Louis DUPONT DE DINECHIN

IPC: G06N20/00 ,  G06F16/22

Abstract: The disclosure notably relates to a computer-implemented method for teaching a generative autoencoder. The generative autoencoder is configured to generate functional structures. A functional structure is a data structure representing a mechanical assembly of rigid parts and which includes a tree. Each leaf node represents a shape and positioning of a respective rigid part and a force exerted on the respective rigid part. Each non-leaf node with several children represents a mechanical link between sub-assemblies. Each sub-assembly is represented by a respective one of the several children. Each non-leaf node with a single child represents a duplication of the sub-assembly represented by the single child. The method includes obtaining a dataset including functional structures. The method further comprises teaching the generative autoencoder on the dataset. This constitutes an improved method for teaching a generative autoencoder configured for generating functional structures.

公开(公告)号：US20210049420A1

公开(公告)日：2021-02-18

申请号：US17086078

申请日：2020-10-30

Applicant: DASSAULT SYSTEMES

Inventor： Louis DUPONT DE DINECHIN ,  Asma REJEB SFAR

IPC: G06K9/62 ,  G06K9/46 ,  G06N20/10 ,  G06T7/70 ,  G06N3/08

Abstract: A computer-implemented method of signal processing comprises providing images. The method comprises for each respective one of at least a subset of the images: applying a weakly-supervised learnt function, the weakly-supervised learnt function outputting respective couples each including a respective localization and one or more respective confidence scores, each confidence score representing a probability of instantiation of a respective object category at the respective localization. The method further comprises determining, based on the output of the weakly-supervised learnt function, one or more respective annotations, each annotation including a respective localization and a respective label representing instantiation a respective object category at the respective localization. The method further comprises forming a dataset including pieces of data, each piece of data including a respective image of the subset and at least a part of the one or more annotations determined for the respective image. This improves the field of object detection.

公开(公告)号：US20190243928A1

公开(公告)日：2019-08-08

申请号：US16235930

申请日：2018-12-28

Applicant: DASSAULT SYSTEMES

Inventor： Asma REJEB SFAR ,  Louis DUPONT DE DINECHIN ,  Malika BOULKENAFED

IPC: G06F17/50 ,  G06N3/08 ,  G06K9/62

CPC classification number: G06F17/5004 ,  G06K9/00476 ,  G06K9/342 ,  G06K9/4628 ,  G06K9/6256 ,  G06K9/627 ,  G06N3/08

Abstract: The disclosure notably relates to a computer-implemented method for determining a function configured to determine a semantic segmentation of a 2D floor plan representing a layout of a building. The method comprises providing a dataset comprising 2D floor plans each associated to a respective semantic segmentation. The method also comprises learning the function based on the dataset. Such a method provides an improved solution for processing a 2D floor plan.