-
公开(公告)号：US11593664B2
公开(公告)日：2023-02-28
申请号：US16917414
申请日：2020-06-30
Inventor： Laurent Folliot , Pierre Demaj , Emanuele Plebani
Abstract: A method can be performed prior to implementation of a neural network by a processing unit. The neural network comprising a succession of layers and at least one operator applied between at least one pair of successive layers. A computational tool generates an executable code intended to be executed by the processing unit in order to implement the neural network. The computational tool generates at least one transfer function between the at least one pair of layers taking the form of a set of pre-computed values.
-
2.发明公开公开(公告)号：US20240119309A1
公开(公告)日：2024-04-11
申请号：US18470798
申请日：2023-09-20
Inventor： Laurent Folliot , Marco Lattuada , Pierre Demaj
CPC classification number: G06N3/10 , G06F8/35 , G06F8/4434
Abstract: In an embodiments a method includes obtaining a neural network (INN), the neural network having a plurality of neural layers, each layer being capable of being executed according to different implementation solutions and impacting a required memory allocation for the execution of the neural network and/or an execution time of the neural network, defining a maximum execution time threshold of the neural network and/or a maximum required memory allocation threshold for the execution of the neural network, determining an optimal required memory allocation size for the execution of the neural network from possible implementation solutions for each layer of the neural network, determining an optimal execution time of the neural network from the possible implementation solutions for each layer of the neural network and estimating a performance loss or a performance gain in terms of execution time and required memory allocation for each implementation solution of each layer of the neural network.
-
公开(公告)号：US11609851B2
公开(公告)日：2023-03-21
申请号：US17229161
申请日：2021-04-13
Inventor： Laurent Folliot , Emanuele Plebani , Mirko Falchetto
Abstract: According to one aspect, a method for determining, for a memory allocation, placements in a memory area of data blocks generated by a neural network, comprises a development of an initial sequence of placements of blocks, each placement being selected from several possible placements, the initial sequence being defined as a candidate sequence, a development of at least one modified sequence of placements from a replacement of a given placement of the initial sequence by a memorized unselected placement, and, if the planned size of the memory area obtained by this modified sequence is less than that of the memory area of the candidate sequence, then this modified sequence becomes the candidate sequence, the placements of the blocks for the allocation being those of the placement sequence defined as a candidate sequence once each modified sequence has been developed.
-
公开(公告)号：US20210342265A1
公开(公告)日：2021-11-04
申请号：US17229161
申请日：2021-04-13
Inventor： Laurent Folliot , Emanuele Plebani , Mirko Falchetto
Abstract: According to one aspect, a method for determining, for a memory allocation, placements in a memory area of data blocks generated by a neural network, comprises a development of an initial sequence of placements of blocks, each placement being selected from several possible placements, the initial sequence being defined as a candidate sequence, a development of at least one modified sequence of placements from a replacement of a given placement of the initial sequence by a memorized unselected placement, and, if the planned size of the memory area obtained by this modified sequence is less than that of the memory area of the candidate sequence, then this modified sequence becomes the candidate sequence, the placements of the blocks for the allocation being those of the placement sequence defined as a candidate sequence once each modified sequence has been developed.
-
公开(公告)号：US20210012208A1
公开(公告)日：2021-01-14
申请号：US16917414
申请日：2020-06-30
Inventor： Laurent Folliot , Pierre Demaj , Emanuele Plebani
Abstract: A method can be performed prior to implementation of a neural network by a processing unit. The neural network comprising a succession of layers and at least one operator applied between at least one pair of successive layers. A computational tool generates an executable code intended to be executed by the processing unit in order to implement the neural network. The computational tool generates at least one transfer function between the at least one pair of layers taking the form of a set of pre-computed values.
-
Patent Agency Ranking
公开(公告)号：US20230409869A1
公开(公告)日：2023-12-21
申请号：US18316152
申请日：2023-05-11
Applicant: STMicroelectronics ( Rousset ) SAS
Inventor： Laurent Folliot , Pierre Demaj
IPC: G06N3/04
CPC classification number: G06N3/04
Abstract: According to one aspect, there is proposed a method for transforming a trained artificial neural network including a binary convolution layer followed by a pooling layer then a batch normalization layer, the method includes obtaining the trained artificial neural network and transforming the trained artificial neural network such that the order of the layers of the trained artificial neural network is modified by displacing the batch normalization layer after the convolution layer.
-
7.发明授权公开(公告)号：US11500767B2
公开(公告)日：2022-11-15
申请号：US16810546
申请日：2020-03-05
Applicant: STMicroelectronics (Rousset) SAS
Inventor： Laurent Folliot , Pierre Demaj
Abstract: In accordance with an embodiment, a method for determining an overall memory size of a global memory area configured to store input data and output data of each layer of a neural network includes: for each current layer of the neural network after a first layer, determining a pair of elementary memory areas based on each preceding elementary memory area associated with a preceding layer, wherein: the two elementary memory areas of the pair of elementary memory areas respectively have two elementary memory sizes, each of the two elementary memory areas are configured to store input data and output data of the current layer of the neural network, the output data is respectively stored in two different locations, and the overall memory size of the global memory area corresponds to a smallest elementary memory size at an output of the last layer of the neural network.
-
8.发明申请公开(公告)号：US20200302278A1
公开(公告)日：2020-09-24
申请号：US16810546
申请日：2020-03-05
Applicant: STMicroelectronics (Rousset) SAS
Inventor： Laurent Folliot , Pierre Demaj
Abstract: In accordance with an embodiment, a method for determining an overall memory size of a global memory area configured to store input data and output data of each layer of a neural network includes: for each current layer of the neural network after a first layer, determining a pair of elementary memory areas based on each preceding elementary memory area associated with a preceding layer, wherein: the two elementary memory areas of the pair of elementary memory areas respectively have two elementary memory sizes, each of the two elementary memory areas are configured to store input data and output data of the current layer of the neural network, the output data is respectively stored in two different locations, and the overall memory size of the global memory area corresponds to a smallest elementary memory size at an output of the last layer of the neural network.
-
9.发明申请公开(公告)号：US20200169631A1
公开(公告)日：2020-05-28
申请号：US16774954
申请日：2020-01-28
Applicant: STMicroelectronics (Rousset) SAS
Inventor： Pierre Demaj , Laurent Folliot
IPC: H04M1/725 , G01D21/02 , H04W4/02 , H04W12/00 , H04W4/029 , H04W52/02 , G06F9/445 , G06F3/01 , G06K9/00
Abstract: A method of real-time scene detection performed by a wireless communication device includes, performing a first scene detection measurement to determine that the wireless communication device is located in a first scene. The first scene detection measurement is performed at first instant in time. The first scene is a type of environment. The method further includes associating the first scene with a corresponding reference scene of a predetermined set of reference scenes, determining a reference duration associated with the corresponding reference scene, and performing a second scene detection measurement immediately following expiration of the reference duration measured from the first instant in time.
-
10.发明申请公开(公告)号：US20230131067A1
公开(公告)日：2023-04-27
申请号：US17968163
申请日：2022-10-18
Applicant: STMicroelectronics (Rousset) SAS
Inventor： Pierre Demaj , Laurent Folliot
Abstract: According to one aspect, a method is proposed for detecting events or elements in physical signals by implementing an artificial neural network. The method includes an assessment of a probability of the presence of the event or the element by an implementation of the neural network. The implementation of the neural network according to a nominal mode takes as input a physical signal having a first resolution, called nominal resolution, when the probability of presence of the event or the element is greater than a threshold. The implementation of the neural network according to a low power mode takes as input a physical signal having a second resolution, called reduced resolution, lower than the first resolution, when the probability of presence of the event or the element is below the threshold.
-
-
-
-
-
-
-
-
-
Search Results
34
records
(took 0.025 seconds)
