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公开(公告)号：US10136393B2
公开(公告)日：2018-11-20
申请号：US15472794
申请日：2017-03-29
摘要： 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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12.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
发明人： Laurent Folliot , Marco Lattuada , Pierre Demaj
CPC分类号： G06N3/10 , G06F8/35 , G06F8/4434
摘要： 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.
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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
发明人： Pierre Demaj , Laurent Folliot
摘要： 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
发明人： Laurent Folliot , Mirko Falchetto , Pierre Demaj
摘要： 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
发明人： Pierre Demaj , Laurent Folliot
摘要： 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
发明人： Pierre Demaj , Laurent Folliot
CPC分类号： G06K9/00684 , G06K9/6256 , G06K9/6265 , G06K9/6268 , G06Q50/10
摘要： 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：US20180070315A1
公开(公告)日：2018-03-08
申请号：US15472794
申请日：2017-03-29
CPC分类号： H04W52/0254 , G06N99/005 , H04L67/22 , H04L67/325 , H04M1/72569 , H04M2250/12 , H04W4/027 , H04W4/043 , H04W4/38 , H04W4/50 , H04W52/0209 , H04W52/0261
摘要： 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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18.发明申请公开(公告)号：US20230131838A1
公开(公告)日：2023-04-27
申请号：US17968148
申请日：2022-10-18
发明人： Pierre Demaj , Laurent Folliot
摘要： 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.
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19.发明申请公开(公告)号：US20230126848A1
公开(公告)日：2023-04-27
申请号：US17968174
申请日：2022-10-18
发明人： Pierre Demaj , Laurent Folliot
IPC分类号： G06N3/04
摘要： 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.
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公开(公告)号：US20220188610A1
公开(公告)日：2022-06-16
申请号：US17455770
申请日：2021-11-19
发明人： Laurent Folliot , Mirko Falchetto , Pierre Demaj
摘要： 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.
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