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公开(公告)号：US11763550B2
公开(公告)日：2023-09-19
申请号：US17086078
申请日：2020-10-30
申请人： DASSAULT SYSTEMES
IPC分类号： G06V10/774 , G06N20/10 , G06T7/70 , G06F18/21 , G06F18/23 , G06F18/28 , G06F18/214 , G06V10/44 , G06V10/24 , G06N3/08
CPC分类号： G06V10/7753 , G06F18/2155 , G06F18/2185 , G06F18/23 , G06F18/28 , G06N3/08 , G06N20/10 , G06T7/70 , G06V10/245 , G06V10/454
摘要： 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.
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公开(公告)号：US11893313B2
公开(公告)日：2024-02-06
申请号：US17124452
申请日：2020-12-16
申请人： DASSAULT SYSTEMES
发明人： Asma Rejeb Sfar , Tom Durand , Malika Boulkenafed
CPC分类号： G06F30/10 , G06N3/08 , G06T7/11 , G06T2207/10028 , G06T2207/20081 , G06T2207/20084 , G06T2207/20101
摘要： A computer-implemented method of machine-learning including obtaining a dataset of 3D point clouds. Each 3D point cloud includes at least one object. Each 3D point cloud is equipped with a specification of one or more graphical user-interactions each representing a respective selection operation of a same object in the 3D point cloud. The method further includes teaching, based on the dataset, a neural network configured for segmenting an input 3D point cloud including an object. The segmenting is based on the input 3D point cloud and on a specification of one or more input graphical user-interactions each representing a respective selection operation of the object in the 3D point cloud.
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公开(公告)号：US11977976B2
公开(公告)日：2024-05-07
申请号：US16868311
申请日：2020-05-06
申请人： DASSAULT SYSTEMES
摘要： A computer-implemented method of machine-learning is described that includes obtaining a test dataset of scenes. The test dataset belongs to a test domain. The method includes obtaining a domain-adaptive neural network. The domain-adaptive neural network is a machine-learned neural network taught using data obtained from a training domain. The domain-adaptive neural network is configured for inference of spatially reconfigurable objects in a scene of the test domain. The method further includes determining an intermediary domain. The intermediary domain is closer to the training domain than the test domain in terms of data distributions. The method further includes inferring, by applying the domain-adaptive neural network, a spatially reconfigurable object from a scene of the test domain transferred on the intermediary domain. Such a method constitutes an improved method of machine learning with a dataset of scenes comprising spatially reconfigurable objects.
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公开(公告)号：US11568109B2
公开(公告)日：2023-01-31
申请号：US16868265
申请日：2020-05-06
申请人： DASSAULT SYSTEMES
IPC分类号： G06F30/27 , G06F30/17 , G06N3/08 , G06N5/04 , G06F111/18 , G06N3/04 , G06N3/00 , G06F111/00 , G06F30/12
摘要： A computer-implemented method of machine-learning is described that includes obtaining a dataset of virtual scenes. The dataset of virtual scenes belongs to a first domain. The method further includes obtaining a test dataset of real scenes. The test dataset belongs to a second domain. The method further includes determining a third domain. The third domain is closer to the second domain than the first domain in terms of data distributions. The method further includes learning a domain-adaptive neural network based on the third domain. The domain-adaptive neural network is a neural network configured for inference of spatially reconfigurable objects in a real scene. Such a method constitutes an improved method of machine learning with a dataset of scenes including spatially reconfigurable objects.
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公开(公告)号：US10176404B2
公开(公告)日：2019-01-08
申请号：US15370997
申请日：2016-12-06
申请人： DASSAULT SYSTEMES
摘要： The invention notably relates to a computer-implemented method for recognizing a three-dimensional modeled object from a two-dimensional image. The method comprises providing a first set of two-dimensional images rendered from three-dimensional modeled objects, each two-dimensional image of the first set being associated to a label; providing a second set of two-dimensional images not rendered from three-dimensional objects, each two-dimensional image of the second set being associated to a label; training a model on both first and second sets; providing a similarity metric; submitting a two-dimensional image depicting at least one object; and retrieving a three-dimensional object similar to the said at least one object of the two-dimensional image submitted by using the trained model and the similarity metric.
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公开(公告)号：US12051261B2
公开(公告)日：2024-07-30
申请号：US16235930
申请日：2018-12-28
申请人： DASSAULT SYSTEMES
IPC分类号： G06F30/13 , G06F18/214 , G06F18/2413 , G06N3/08 , G06V10/26 , G06V10/44 , G06V10/764 , G06V10/82 , G06V30/422
CPC分类号： G06V30/422 , G06F18/214 , G06F18/2413 , G06F30/13 , G06N3/08 , G06V10/267 , G06V10/454 , G06V10/764 , G06V10/82
摘要： 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.
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公开(公告)号：US11636234B2
公开(公告)日：2023-04-25
申请号：US16234927
申请日：2018-12-28
申请人： DASSAULT SYSTEMES
摘要： The disclosure notably relates to a computer-implemented method for generating a 3D model representing a building. The method comprises providing a 2D floor plan representing a layout of the building. The method also comprises determining a semantic segmentation of the 2D floor plan. The method also comprises determining the 3D model based on the semantic segmentation. Such a method provides an improved solution for processing a 2D floor plan.
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公开(公告)号：US10929721B2
公开(公告)日：2021-02-23
申请号：US15973165
申请日：2018-05-07
申请人： DASSAULT SYSTEMES
摘要： 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.
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