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公开(公告)号：US20250062845A1
公开(公告)日：2025-02-20
申请号：US18724211
申请日：2022-12-14
Applicant: Telecom Italia S.p.A.
Inventor： Simone BIZZARRI , Gianluca FRANCINI , Giorgio GHINAMO , Giuseppe MINERVA
IPC: H04B17/391 , H04B17/382 , H04W24/04
Abstract: A method for configuring a cellular network including measuring values of at least one performance indicator over a plurality of time intervals, the plurality of time intervals comprising a current time interval and a plurality of historical time intervals; determining, for each historical time interval, a plurality of alternative network configurations; determining, for each alternative network configuration, simulated values of the at least one performance indicator; based on the measured historical and simulated values of the at least one performance indicator, determining, for each selected historical time interval, a best network configuration; based on the current and measured historical values of the at least one performance indicator, determining forecast values of the at least one performance indicator for a following time interval; based on the forecast values, predicting an optimal network configuration for the following time interval and configuring the cellular network according to the predicted optimal network configuration.
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Patent Agency Ranking
公开(公告)号：US20200042871A1
公开(公告)日：2020-02-06
申请号：US16081693
申请日：2016-03-11
Applicant: TELECOM ITALIA S.p.A.
Inventor： Gianluca FRANCINI , Skjalg LEPSOY , Pedro PORTO BUARQUE DE GUSMAO
Abstract: A method in which a convolutional neural network is configured to receive an input data structure including a group of values corresponding to signal samples and to generate a corresponding classification output indicative of a selected one among plural predefined classes. The convolutional neural network includes an ordered sequence of layers, each configured to receive a corresponding layer input data structure including a group of input values, and generate a corresponding layer output data structure including a group of output values by convolving the layer input data structure with at least one corresponding filter including a corresponding group of weights. The layer input data structure of the first layer of the sequence corresponds to the input data structure. The layer input data structure of a generic layer of the sequence different from the first layer corresponds to the layer output data structure generated by a previous layer in the sequence.
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公开(公告)号：US20170249516A1
公开(公告)日：2017-08-31
申请号：US15516965
申请日：2014-10-13
Applicant: TELECOM ITALIA S.p.A.
Inventor： Skjalg LEPSØY , Massimo BALESTRI , Gianluca FRANCINI
CPC classification number: G06K9/00758 , G06K9/6211 , G06K9/6215
Abstract: A method (100) for comparing a first video shot (Vs1) comprising a first set of first images (I1(s)) with a second video shot (Vs2) comprising a second set of second images (I2(t)), at least one between the first and the second set comprising at least two images. The method comprises pairing (110) each first image of the first set with each second image of the second set to form a plurality of images pairs (IP(m)), and, for each image pair, carrying out the operations a)-g): a) identifying (120) first interest points in the first image and second interest points in the second image; b) associating (120) first interest points with corresponding second interest points in order to form corresponding interest point matches; c) for each pair of first interest points, calculating (130) the distance therebetween for obtaining a corresponding first length; d) for each pair of second interest points, calculating (130) the distance therebetween for obtaining a corresponding second length; e) calculating a plurality of distance ratios (130), each distance ratio corresponding to a selected pair of interest point matches and being based on a ratio of a first term and a second term or on a ratio of the second term and the first term, said first term corresponding to the distance between the first interest points of said pair of interest point matches and said second term corresponding to the distance between the second interest points of said pair of interest point matches; f) computing (140) a first representation of the statistical distribution of the plurality of calculated distance ratios; g) computing (150) a second representation of the statistical distribution of distance ratios obtained under the hypothesis that all the interest point matches in the image pair are outliers. The method further comprises generating (160) a first global representation of the statistical distribution of the plurality of calculated distance ratios computed for all the image pairs based on the first representations of all the image pairs; generating (170) a second global representation of the statistical distribution of distance ratios obtained under the hypothesis that all the interest point matches in all the image pairs are outliers based on the second representations of all the image pairs; comparing (180) said first global representation with said second global representation, and assessing (190) whether the first video shot contains a view of an object depicted in the second video shot based on said comparison.
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公开(公告)号：US20160155014A1
公开(公告)日：2016-06-02
申请号：US14906218
申请日：2014-07-23
Applicant: TELECOM ITALIA S.P.A.
Inventor： Massimo BALESTRI , Gianluca FRANCINI , Skjalg LEPSOY
IPC: G06K9/46
CPC classification number: G06K9/4671 , G06K9/4609 , G06K9/4652
Abstract: A method for identifying keypoints in a digital image including a set of pixels. Each pixel has associated thereto a respective value of an image representative parameter. The method includes approximating a filtered image. The filtered image depends on a filtering parameter and includes for each pixel of the image a filtering function that depends on the filtering parameter to calculate a filtered value of the value of the representative parameter of the pixel. The approximating includes: a) generating a set of base filtered images; each base filtered image is the image filtered with a respective value of the filtering parameter; b) for each pixel of at least a subset of the set of pixels, approximating the filtering function by a respective approximation function based on the base filtered images; the approximation function is a function of the filtering parameter within a predefined range of the filtering parameter.
Abstract translation: 一种用于识别包括一组像素的数字图像中的关键点的方法。 每个像素与其相关联地具有图像代表参数的相应值。 该方法包括近似滤波图像。 滤波后的图像取决于滤波参数，并且对于图像的每个像素包括依赖于滤波参数的滤波函数，以计算像素的代表性参数的值的滤波值。 近似值包括：a）生成一组基本滤波图像; 每个基本过滤图像是用过滤参数的相应值过滤的图像; b）对于所述像素集合的至少一个子集的每个像素，通过基于所述基本滤波图像的相应近似函数近似所述滤波函数; 近似函数是过滤参数的预定义范围内的过滤参数的函数。
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公开(公告)号：US20240064531A1
公开(公告)日：2024-02-22
申请号：US18259315
申请日：2021-12-20
Applicant: TELECOM ITALIA S.p.A.
Inventor： Simone BIZZARRI , Gianluca FRANCINI , Giorgio GHINAMO , Giuseppe MINERVA
Abstract: A method for configuring a cellular network comprising a plurality of network cells. The method comprises:
monitoring, during a monitoring time period, a performance indicator of each network cell for each one of a plurality of monitoring time intervals of said monitoring time period;
determining a plurality of sets of measured signal levels, wherein each set of measured signal levels is associated with a respective territorial portion of a geographic area covered by the cellular network, and wherein each measured signal level of each set of measured signal levels is associated with a respective measured network cell, among the plurality of network cells, at least partially within that territorial portion, with a respective cell configuration of said measured network cell, and with a respective monitoring time interval;
determining, for each measured network cell, a simulated signal level being indicative of an expected signal level for that measured network cell in the respective cell configuration;
determining, for each measured network cell and for each monitoring time interval, a signal level deviation as a difference between the respective measured signal level and the respective simulated signal level;
for a reference network configuration (RNC1) including, for each measured network cell, a respective reference cell configuration taken by that measured network cell after the monitoring time period:
(i) determining, for each measured network cell, a reference simulated signal level indicative of an expected signal level for that measured network cell in the reference cell configuration;
(ii) updating, for each monitoring time interval, each measured signal level according to the respective simulated signal level and to the respective signal level deviation;
(iii) determining, for each measured network cell and for each monitoring time interval, an estimated performance indicator based on the respective performance indicator, on a number of sets of measured signal levels having at least one measured signal level associated with said measured network cell, and on the respective updated measured signal level, and
configuring the cellular network according to the estimated performance indicators determined for the measured network cells.-
公开(公告)号：US20210142175A1
公开(公告)日：2021-05-13
申请号：US17251508
申请日：2019-07-18
Applicant: TELECOM ITALIA S.p.A.
Inventor： Attilio FIANDROTTI , Gianluca FRANCINI , Skjalg LEPSOY , Enzo TARTAGLIONE
Abstract: A method includes providing a neural network having a set of weights. The neural network receives an input data structure for generating a corresponding output array according to values of the set of weights. The neural network is trained to obtain a trained neural network. The training includes setting values of the set of weights with a gradient descent algorithm which exploits a cost function including a loss term and a regularization term. The trained neural network is deployed on a device through a communication network, and used by the device. The regularization term is based on a rate of change of elements of the output array caused by variations of the set of weights values.
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