公开(公告)号：US11354238B2

公开(公告)日：2022-06-07

申请号：US16691957

申请日：2019-11-22

Applicant: STMicroelectronics (Rousset) SAS

Inventor： Laurent Folliot ,  Pierre Demaj

IPC: G06N3/04 ,  G06F12/02 ,  G06F12/06

Abstract: A method can be used to determine an overall memory size of a global memory area to be allocated in a memory intended to store input data and output data from each layer of a neural network. An elementary memory size of an elementary memory area intended to store the input data and the output data from the layer is determined for each layer. The elementary memory size is in the range between a memory size for the input data or output data from the layer and a size equal to the sum of the memory size for the input data and the memory size for the output data from the layer. The overall memory size is determined based on the elementary memory sizes associated with the layers. The global memory area contains all the elementary memory areas.

公开(公告)号：US10863018B2

公开(公告)日：2020-12-08

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 ,  H04W4/38 ,  H04W56/00 ,  H04W4/33 ,  H04W4/23

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.

公开(公告)号：US20200302266A1

公开(公告)日：2020-09-24

申请号：US16810582

申请日：2020-03-05

Applicant: STMicroelectronics (Rousset) SAS

Inventor： Pierre Demaj ,  Laurent Folliot

IPC: G06N3/04

Abstract: In accordance with an embodiment, a method includes reducing a size of at least one initial parameter of each layer of an initial multilayer neural network to obtain for each layer a set of new parameters defining a new neural network, wherein each new parameter of the set of new parameters has its data represented in two portions comprising an integer portion and a fractional portion; implementing the new neural network using a test input data set applied only once to each layer; determining a distribution function or a density function resulting from the set of new parameters for each layer; and based on the determined distribution function or density function, adjusting a size of a memory area allocated to the fractional portion and a size of the memory area allocated to the integer portion of each new parameter associated with each layer.

公开(公告)号：US20200183834A1

公开(公告)日：2020-06-11

申请号：US16691957

申请日：2019-11-22

Applicant: STMicroelectronics (Rousset) SAS

Inventor： Laurent Folliot ,  Pierre Demaj

IPC: G06F12/06 ,  G06N3/04

Abstract: A method can be used to determine an overall memory size of a global memory area to be allocated in a memory intended to store input data and output data from each layer of a neural network. An elementary memory size of an elementary memory area intended to store the input data and the output data from the layer is determined for each layer. The elementary memory size is in the range between a memory size for the input data or output data from the layer and a size equal to the sum of the memory size for the input data and the memory size for the output data from the layer. The overall memory size is determined based on the elementary memory sizes associated with the layers. The global memory area contains all the elementary memory areas.

公开(公告)号：US10136393B2

公开(公告)日：2018-11-20

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

IPC: H04W52/02 ,  H04M1/725 ,  H04W4/02 ,  H04W4/04 ,  H04W4/50 ,  H04W4/38 ,  H04L29/08 ,  G06N99/00

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.

公开(公告)号：US20230131838A1

公开(公告)日：2023-04-27

申请号：US17968148

申请日：2022-10-18

Applicant: STMicroelectronics (Rousset) SAS

Inventor： Pierre Demaj ,  Laurent Folliot

IPC: G06V10/62 ,  G06V10/44 ,  G06K9/00

Abstract: According to one aspect, the disclosure proposes a method for detecting events or features in physical signals by implementing an artificial neural network. The method includes evaluating the probability of presence of the event or feature by implementing the artificial neural network. The method includes implementing the artificial neural network in a nominal mode and to which a physical signal having a first so-called nominal resolution is fed, as long as the probability of the presence of the event or feature is below a threshold. The method further includes implementing the artificial neural network in a reduced consumption mode with a reduced resolution, as long as the probability of the presence of the event or feature is above the threshold. The reduced resolution is lower than the first resolution.

公开(公告)号：US20230126848A1

公开(公告)日：2023-04-27

申请号：US17968174

申请日：2022-10-18

Applicant: STMicroelectronics (Rousset) SAS

Inventor： Pierre Demaj ,  Laurent Folliot

IPC: G06N3/04

Abstract: According to one aspect, a method is provided for detecting events or elements in physical signals, including at least one implementation of a reference artificial neural network, at least one implementation of an auxiliary artificial neural network distinct from the reference artificial neural network. The auxiliary artificial neural network being simplified relative to the reference artificial neural network. At least one assessment of a probability of presence of the event or the element by the implementation of the reference artificial neural network or by the implementation of the auxiliary artificial neural network, where the reference artificial neural network is implemented when the probability of presence of the event or the element is greater than a threshold, and wherein the auxiliary artificial neural network is implemented when the probability of presence of the event or the element is below the threshold.

公开(公告)号：US20220188610A1

公开(公告)日：2022-06-16

申请号：US17455770

申请日：2021-11-19

Applicant: STMicroelectronics S.r.I. ,  STMicroelectronics (Rousset) SAS

Inventor： Laurent Folliot ,  Mirko Falchetto ,  Pierre Demaj

IPC: G06N3/063 ,  G06N3/04 ,  G06F12/02

Abstract: According to an aspect, a method is proposed for defining placements, in a volatile memory, of temporary scratch buffers used during an execution of an artificial neural network, the method comprising: determining an execution order of layers of the neural network, defining placements, in a heap memory zone of the volatile memory, of intermediate result buffers generated by each layer, according to the execution order of the layers, determining at least one free area of the heap memory zone over the execution of the layers, defining placements of temporary scratch buffers in the at least one free area of the heap memory zone according to the execution order of the layers.

公开(公告)号：US10929724B2

公开(公告)日：2021-02-23

申请号：US15924608

申请日：2018-03-19

Applicant: STMicroelectronics (Rousset) SAS

Inventor： Pierre Demaj ,  Laurent Folliot

IPC: G06K9/62 ,  G06K9/00

Abstract: A method is provided for monitoring scene detection by an apparatus detecting scenes from among a set of possible reference scenes. It includes an assignment of an identifier to each reference scene, detection of scenes from among the set of possible reference scenes at successive instants of detection with the aid of at least one classification algorithm, and a sliding time filtering processing of these detected current scenes over a filtering window of size M, based on the identifier of each new detected current scene taken into account in the window and a confidence probability associated with this new detected current scene, the output of the filtering processing successively delivering filtered detected scenes.

公开(公告)号：US20200175373A1

公开(公告)日：2020-06-04

申请号：US16680840

申请日：2019-11-12

Applicant: STMicroelectronics (Rousset) SAS

Inventor： Pierre Demaj ,  Laurent Folliot

IPC: G06N3/08 ,  G06N3/04

Abstract: A method can be used with a neural network being implemented by a system having a computation unit coupled to a collection of memories. The method includes analyzing a set of initial parameters defining an initial multilayer neural network. The analyzing includes attempting to reduce an initial memory size of an initial parameter so as to obtain a set of modified parameters defining a modified neural network with respect to the initial network.