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21.发明授权公开(公告)号：US10560564B2
公开(公告)日：2020-02-11
申请号：US15799152
申请日：2017-10-31
Applicant: STMicroelectronics (Rousset) SAS
Inventor： Pierre Demaj , Laurent Folliot
IPC: H04M1/725 , G01D21/02 , H04W4/02 , H04W12/00 , H04W4/029 , H04W52/02 , H04W4/38 , H04W56/00 , H04W4/33 , H04W4/23
Abstract: A method can be used for managing a real-time detection related to a scene. A succession of steps of scene detection is spaced apart by time intervals. A time interval separating a current step of scene detection from a previous step of scene detection is adjusted according to an adjustment criterion linked to a previous scene actually detected. The succession of steps and the adjustment are performed by a wireless communication apparatus.
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公开(公告)号：US11645519B2
公开(公告)日：2023-05-09
申请号：US16691914
申请日：2019-11-22
Applicant: STMicroelectronics (Rousset) SAS
Inventor： Pierre Demaj , Laurent Folliot
CPC classification number: G06N3/08 , G06F17/16 , G06N3/02 , G06N3/045 , G06N3/0464 , G06N3/063 , G06N20/00
Abstract: A method can be used to process an initial set of data through a convolutional neural network that includes a convolution layer followed by a pooling layer. The initial set is stored in an initial memory along first and second orthogonal directions. The method includes performing a first filtering of the initial set of data by the convolution layer using a first sliding window along the first direction. Each slide of the first window produces a first set of data. The method also includes performing a second filtering of the first sets of data by the pooling layer using a second sliding window along the second direction.
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公开(公告)号：US20220107990A1
公开(公告)日：2022-04-07
申请号：US17480639
申请日：2021-09-21
Inventor： Laurent Folliot , Mirko Falchetto , Pierre Demaj
Abstract: In an embodiment a method for managing a convolutional calculation carried out by a calculation unit adapted to calculate output data on output channels from convolution kernels applied to input data blocks on at least one input channel, wherein calculations on each input data block correspond respectively to an output datum on an output channel, and wherein the calculations with each convolution kernel correspond to the output data on each output channel respectively includes identifying a size of a memory location available in a temporary working memory of the calculation unit, pre-loading in the temporary working memory a maximum number of convolution kernels storable at the size of the memory; and controlling the calculation unit to calculate a set of output data calculable from pre-loaded convolution kernels.
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公开(公告)号：US10789477B2
公开(公告)日：2020-09-29
申请号：US15936587
申请日：2018-03-27
Applicant: STMicroelectronics (Rousset) SAS
Inventor： Pierre Demaj , Laurent Folliot
Abstract: A method for real-time detection of at least one scene by an apparatus, from among a set of possible reference scenes, includes acquiring current values of attributes from measurement values supplied by sensors. The method further includes traversing a path through a decision tree. The nodes of the decision tree are respectively associated with the attributes. The traversal considers at each node along the path, the current value of the corresponding attribute, so as to obtain at the output of the path, a scene from among the set of reference scenes. The obtained scene identifying which reference scene is the detected scene. The method further includes developing a confidence index (SC) associated with the identification of the detected scene.
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公开(公告)号：US20180293441A1
公开(公告)日：2018-10-11
申请号：US15936587
申请日：2018-03-27
Applicant: STMicroelectronics (Rousset) SAS
Inventor： Pierre Demaj , Laurent Folliot
CPC classification number: G06K9/00684 , G06K9/6256 , G06K9/6265 , G06K9/6268 , G06Q50/10
Abstract: A method for real-time detection of at least one scene by an apparatus, from among a set of possible reference scenes, includes acquiring current values of attributes from measurement values supplied by sensors. The method further includes traversing a path through a decision tree. The nodes of the decision tree are respectively associated with the attributes. The traversal considers at each node along the path, the current value of the corresponding attribute, so as to obtain at the output of the path, a scene from among the set of reference scenes. The obtained scene identifying which reference scene is the detected scene. The method further includes developing a confidence index (SC) associated with the identification of the detected scene.
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Patent Agency Ranking
公开(公告)号：US20180070315A1
公开(公告)日：2018-03-08
申请号：US15472794
申请日：2017-03-29
Applicant: STMicroelectronics (Rousset) SAS , STMicroelectronics SA
Inventor： Pierre Demaj , Matthieu Durnerin , Laurent Folliot , Ludovic Champsaur
CPC classification number: H04W52/0254 , G06N99/005 , H04L67/22 , H04L67/325 , H04M1/72569 , H04M2250/12 , H04W4/027 , H04W4/043 , H04W4/38 , H04W4/50 , H04W52/0209 , H04W52/0261
Abstract: A control method for real-time scene detection by a wireless communication apparatus equipped with at least one environmental measurement sensor is disclosed. A temporal adjustment of the instants of activation of the detection is based on measurement values delivered by the at least one environmental measurement sensor at instants of measurement.
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公开(公告)号：US20240095502A1
公开(公告)日：2024-03-21
申请号：US18470281
申请日：2023-09-19
Applicant: STMicroelectronics (Rousset) SAS
Inventor： Pierre Demaj , Laurent Folliot
IPC: G06N3/0464
CPC classification number: G06N3/0464
Abstract: An artificial neural network includes a unit cell. The unit cell includes a first binary two-dimensional convolution layer configured to receive an input tensor and to generate a first tensor. A first batch normalization layer is configured to receive the first tensor and to generate a second tensor. A concatenation layer is configured to generate a third tensor by concatenating the input tensor and the second tensor. A second binary two-dimensional convolution layer is configured to receive the third tensor and to generate a fourth tensor. A second batch normalization layer is configured to generate an output tensor based on the fourth tensor.
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公开(公告)号：US11568515B2
公开(公告)日：2023-01-31
申请号：US17361783
申请日：2021-06-29
Inventor： Julien Closs , Jean-Michel Delorme , Daniel Fauvarque , Laurent Folliot , Guillaume Legrain
Abstract: An embodiment method for converting an initial digital image into a converted digital image, electronic chip, system and computer program product are disclosed, the initial digital image comprising a set of pixels, the pixels being associated respectively with colors, the initial digital image being acquired by an acquisition device, and the converted digital image able to be used by a neural network. The embodiment method comprises redimensioning of the initial digital image in order to obtain an intermediate digital image, the redimensioning being carried out by a reduction in the number of pixels of the initial image, modification of a format of one of the pixels of the intermediate digital image in order to obtain a converted digital image, the modification being carried out, after the redimensioning, by increasing the number of bits used to represent the color of the pixel.
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公开(公告)号：US20220164664A1
公开(公告)日：2022-05-26
申请号：US17510273
申请日：2021-10-25
Applicant: STMicroelectronics (Rousset) SAS
Inventor： Pierre Demaj , Laurent Folliot
Abstract: According to one aspect, the disclosure proposes a method for updating an artificial neural network including initial weights stored in a memory at least in an integer format, which method includes: a processing unit determining the error gradients at the output of the layers of the neural network, the processing unit retrieving the initial weights from memory, the processing unit updating the initial weights comprising, for each initial weight, a first calculation of a corrected weight, in the integer format of this initial weight, the processing unit replacing the value of the initial weights stored in the memory by the value of the corrected weights.
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公开(公告)号：US20210407040A1
公开(公告)日：2021-12-30
申请号：US17361783
申请日：2021-06-29
Inventor： Julien Closs , Jean-Michel Delorme , Daniel Fauvarque , Laurent Folliot , Guillaume Legrain
IPC: G06T3/40
Abstract: An embodiment method for converting an initial digital image into a converted digital image, electronic chip, system and computer program product are disclosed, the initial digital image comprising a set of pixels, the pixels being associated respectively with colors, the initial digital image being acquired by an acquisition device, and the converted digital image able to be used by a neural network. The embodiment method comprises redimensioning of the initial digital image in order to obtain an intermediate digital image, the redimensioning being carried out by a reduction in the number of pixels of the initial image, modification of a format of one of the pixels of the intermediate digital image in order to obtain a converted digital image, the modification being carried out, after the redimensioning, by increasing the number of bits used to represent the color of the pixel.
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