Patents by Inventor Danilo Pietro Pau

Danilo Pietro Pau has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).

  • Publication number: 20250005319
    Abstract: Methods, apparatuses, systems, and/or computer program products for using a neural network splitter to split a neural network into slices are provided. A splitter device may receive a neural network. The splitter devices may be connected to one or more other devices. The neural network may be split the neural network into slices to be deployed to the one or more other devices for execution. The neural network splitter may generate and intermediate representation of the neural network. A profiler of the neural network splitter may extract one or more features from the intermediate representation. A classifier may select one or more heuristics of the neural network features. The neural network may then determine one or more slices based on the features, heuristics, and device characteristics of the connected devices. The slices may be generated and deployed to the connected devices for execution.
    Type: Application
    Filed: June 27, 2023
    Publication date: January 2, 2025
    Inventors: Danilo Pietro Pau, Biagio MONTARULI, Andrea SANTAMARIA
  • Patent number: 12158533
    Abstract: A device includes a memory and processing circuitry coupled to the memory. The processing circuitry, in operation, generates an indication of a predicted difference in a direction of arrival (DoA) of a signal using a trained autoregressive model. A predicted indication of a DoA of the signal is generated based on a previous indication of the DoA of the signal and the indication of the predicted difference in the DoA of the signal. The processing circuitry actuates or controls an antenna array based on predicted indications of the DoA of the signal.
    Type: Grant
    Filed: August 30, 2021
    Date of Patent: December 3, 2024
    Assignees: STMICROELECTRONICS S.r.l., STMICROELECTRONICS INTERNATIONAL N.V.
    Inventors: Danilo Pietro Pau, Alessandro Cremonesi
  • Publication number: 20240265249
    Abstract: Methods, apparatuses, systems, and computer program products for artificial intelligence and machine learning for resource constrained devices and systems, including for classifier learning from a stream of data. A classifier may include a neural network comprised of a plurality of layers with each layer comprised of a plurality of neurons. The neural network may include a hidden layer comprised of a plurality of hidden neurons. In various embodiments, the size of the hidden layer may be constrained and the training of a hidden layer included removing one or more hidden neurons from the hidden layer.
    Type: Application
    Filed: February 3, 2023
    Publication date: August 8, 2024
    Inventors: Danilo Pietro Pau, Prem Kumar Ambrose
  • Patent number: 11960988
    Abstract: A classification device receives sensor data from a set of sensors and generates, using a context classifier having a set of classifier model parameters, a set of raw predictions based on the received sensor data. Temporal filtering and heuristic filtering are applied to the raw predictions, producing filtered predictions. A prediction error is generated from the filtered predictions, and model parameters of the set of classifier model parameters are updated based on said prediction error. The classification device may be a wearable device.
    Type: Grant
    Filed: February 23, 2018
    Date of Patent: April 16, 2024
    Assignee: STMICROELECTRONICS S.r.l.
    Inventors: Emanuele Plebani, Danilo Pietro Pau
  • Publication number: 20230068500
    Abstract: A device includes a memory and processing circuitry coupled to the memory. The processing circuitry, in operation, generates an indication of a predicted difference in a direction of arrival (DoA) of a signal using a trained autoregressive model. A predicted indication of a DoA of the signal is generated based on a previous indication of the DoA of the signal and the indication of the predicted difference in the DoA of the signal. The processing circuitry actuates or controls an antenna array based on predicted indications of the DoA of the signal.
    Type: Application
    Filed: August 30, 2021
    Publication date: March 2, 2023
    Inventors: Danilo Pietro PAU, Alessandro CREMONESI
  • Patent number: 11537840
    Abstract: A neural network classifies an input signal. For example, an accelerometer signal may be classified to detect human activity. In a first convolutional layer, two-valued weights are applied to the input signal. In a first two-valued function layer coupled at input to an output of the first convolutional layer, a two-valued function is applied. In a second convolutional layer coupled at input to an output of the first two-valued functional layer, weights of the second convolutional layer are applied. In a fully-connected layer coupled at input to an output of the second convolutional layer, two-valued weights of the fully connected layer are applied. In a second two-valued function layer coupled at input to an output of the fully connected layer, a two-valued function of the second two-valued function layer is applied. A classifier classifies the input signal based on an output signal of second two-valued function layer.
    Type: Grant
    Filed: November 13, 2018
    Date of Patent: December 27, 2022
    Assignee: STMICROELECTRONICS S.R.L.
    Inventors: Danilo Pietro Pau, Emanuele Plebani, Fabio Giuseppe De Ambroggi, Floriana Guido, Angelo Bosco
  • Patent number: 11475238
    Abstract: An image processing system has one or more memories and image processing circuitry coupled to the one or more memories. The image processing circuitry, in operation, compares a first image to feature data in a comparison image space using a matching model. The comparing includes: unwarping keypoints in keypoint data of the first image; and comparing the unwarped keypoints and descriptor data associated with the first image to the feature data of the comparison image. The image processing circuitry determines whether the first image matches the comparison image based on the comparing.
    Type: Grant
    Filed: January 24, 2020
    Date of Patent: October 18, 2022
    Assignee: STMICROELECTRONICS S.r.l.
    Inventors: Arcangelo Ranieri Bruna, Danilo Pietro Pau
  • Patent number: 11461142
    Abstract: Methods, microprocessors, and systems are provided for implementing an artificial neural network. Data buffers in virtual memory are coupled to respective processing layers in the artificial neural network. An ordered visiting sequence of layers of the artificial neural network is obtained. A virtual memory allocation schedule is produced as a function of the ordered visiting sequence of layers of the artificial neural network, the schedule including a set of instructions for memory allocation and deallocation operations applicable to the data buffers. A physical memory configuration dataset is computed as a function of the virtual memory allocation schedule for the artificial neural network, the dataset including sizes and addresses of physical memory locations for the artificial neural network.
    Type: Grant
    Filed: July 8, 2020
    Date of Patent: October 4, 2022
    Assignee: STMICROELECTRONICS S.r.l.
    Inventors: Emanuele Plebani, Mirko Falchetto, Danilo Pietro Pau
  • Publication number: 20210026695
    Abstract: Methods, microprocessors, and systems are provided for implementing an artificial neural network. Data buffers in virtual memory are coupled to respective processing layers in the artificial neural network. An ordered visiting sequence of layers of the artificial neural network is obtained. A virtual memory allocation schedule is produced as a function of the ordered visiting sequence of layers of the artificial neural network, the schedule including a set of instructions for memory allocation and deallocation operations applicable to the data buffers. A physical memory configuration dataset is computed as a function of the virtual memory allocation schedule for the artificial neural network, the dataset including sizes and addresses of physical memory locations for the artificial neural network.
    Type: Application
    Filed: July 8, 2020
    Publication date: January 28, 2021
    Inventors: Emanuele PLEBANI, Mirko FALCHETTO, Danilo Pietro PAU
  • Publication number: 20200160102
    Abstract: An image processing system has one or more memories and image processing circuitry coupled to the one or more memories. The image processing circuitry, in operation, compares a first image to feature data in a comparison image space using a matching model. The comparing includes: unwarping keypoints in keypoint data of the first image; and comparing the unwarped keypoints and descriptor data associated with the first image to the feature data of the comparison image. The image processing circuitry determines whether the first image matches the comparison image based on the comparing.
    Type: Application
    Filed: January 24, 2020
    Publication date: May 21, 2020
    Inventors: Arcangelo Ranieri BRUNA, Danilo Pietro PAU
  • Patent number: 10585937
    Abstract: Local descriptors are extracted from digital image information and digital depth information related to digital images. The local descriptors convey appearance description information and shape description information related to the digital images. Global representations of the one or more digital images are generated based on the extracted local descriptors, and are hashed. Visual search queries are generated based on the hashed global representations. The visual search queries include fused appearance description information and shape description information conveyed in the local descriptors. The fusing may occur before the global representations are generated, before the hashing or after the hashing.
    Type: Grant
    Filed: March 15, 2016
    Date of Patent: March 10, 2020
    Assignee: STMICROELECTRONICS S.R.L.
    Inventors: Danilo Pietro Pau, Alioscia Petrelli, Luigi Di Stefano
  • Patent number: 10579904
    Abstract: Apparatus and methods to unwarp at least portions of distorted, electronically-captured images are described. Keypoints, instead of an entire image, may be unwarped and used in various machine-vision algorithms, such as object recognition, image matching, and 3D reconstruction algorithms. When using unwarped keypoints, the machine-vision algorithms may perform reliably irrespective of distortions that may be introduced by one or more image capture systems.
    Type: Grant
    Filed: April 24, 2013
    Date of Patent: March 3, 2020
    Assignee: STMICROELECTRONICS S.R.L.
    Inventors: Arcangelo Ranieri Bruna, Danilo Pietro Pau
  • Patent number: 10489681
    Abstract: Digital image processing circuitry clusters a set of images into a set of first clusters of images and a set of unclustered images. The set of first clusters are merged, generating a set of second clusters of images. Images in the set of unclustered images are assigned to one of a cluster of the set of second clusters of images and an outlier image cluster. The clustered images may be partitioned into subclusters based on detection of objects in the images.
    Type: Grant
    Filed: December 3, 2015
    Date of Patent: November 26, 2019
    Assignee: STMICROELECTRONICS S.R.L.
    Inventors: Danilo Pietro Pau, Emanuele Plebani, Luca Paliotto
  • Patent number: 10445613
    Abstract: First and second video frames in a flow of digital video frames are encoded by extracting respective sets of keypoints and descriptors, each descriptor including a plurality of orientation histograms regarding a patch of pixels centered on the respective keypoint. Once a pair of linked descriptors has been identified, one for each frame, which have a minimum distance from among the distances between any one of the descriptors of the first frame and any one of the descriptors of the second frame, the differences of the histograms of the descriptors linked in the pair are calculated, and the descriptors linked in the pair are encoded as the set including one of the linked descriptors and the histogram differences by subjecting the histogram differences to a thesholding setting at zero all the differences below a certain threshold, to quantization, and to run-length encoding.
    Type: Grant
    Filed: October 11, 2013
    Date of Patent: October 15, 2019
    Assignee: STMicroelectronics S.r.l.
    Inventor: Danilo Pietro Pau
  • Patent number: 10330779
    Abstract: A laserbeam light source is controlled to avoid light sensitive regions around the laserbeam light source. One or more laserlight-sensitive regions are identified based on images of an area around the laserbeam light source, and indications of positions corresponding to the laserlight-sensitive regions are generated. The laserbeam light source is controlled based on the indications of the positions. The laserbeam light source may be controlled to deflect a laserlight beam away from laserlight-sensitive regions, to reduce an intensity of a laserlight beam directed towards a laserlight-sensitive region, etc. Motion estimation may be used to generate the indications of positions corresponding to the laserlight-sensitive regions.
    Type: Grant
    Filed: August 31, 2017
    Date of Patent: June 25, 2019
    Assignee: STMICROELECTRONICS S.r.l.
    Inventors: Danilo Pietro Pau, Emanuele Plebani
  • Publication number: 20190147338
    Abstract: A neural network classifies an input signal. For example, an accelerometer signal may be classified to detect human activity. In a first convolutional layer, two-valued weights are applied to the input signal. In a first two-valued function layer coupled at input to an output of the first convolutional layer, a two-valued function is applied. In a second convolutional layer coupled at input to an output of the first two-valued functional layer, weights of the second convolutional layer are applied. In a fully-connected layer coupled at input to an output of the second convolutional layer, two-valued weights of the fully connected layer are applied. In a second two-valued function layer coupled at input to an output of the fully connected layer, a two-valued function of the second two-valued function layer is applied. A classifier classifies the input signal based on an output signal of second two-valued function layer.
    Type: Application
    Filed: November 13, 2018
    Publication date: May 16, 2019
    Inventors: Danilo Pietro PAU, Emanuele PLEBANI, Fabio Giuseppe DE AMBROGGI, Floriana GUIDO, Angelo BOSCO
  • Publication number: 20180322393
    Abstract: A neural network includes one layer of neurons including neurons having neuron connections to neurons in the layer and input connections to a network input. The neuron connections and the input connections have respective neuron connection weights and input connection weights. The neurons have neuron responses set by an activation function with activation values and include activation function computing circuits configured for computing current activation values of the activation function as a function of previous activation values of the activation function and current network input values.
    Type: Application
    Filed: April 27, 2018
    Publication date: November 8, 2018
    Inventors: Danilo Pietro PAU, Marco PIASTRA, Luca CARCANO
  • Publication number: 20180247194
    Abstract: A classification device receives sensor data from a set of sensors and generates, using a context classifier having a set of classifier model parameters, a set of raw predictions based on the received sensor data. Temporal filtering and heuristic filtering are applied to the raw predictions, producing filtered predictions. A prediction error is generated from the filtered predictions, and model parameters of the set of classifier model parameters are updated based on said prediction error. The classification device may be a wearable device.
    Type: Application
    Filed: February 23, 2018
    Publication date: August 30, 2018
    Inventors: Emanuele PLEBANI, Danilo Pietro PAU
  • Publication number: 20180246188
    Abstract: A laserbeam light source is controlled to avoid light sensitive regions around the laserbeam light source. One or more laserlight-sensitive regions are identified based on images of an area around the laserbeam light source, and indications of positions corresponding to the laserlight-sensitive regions are generated. The laserbeam light source is controlled based on the indications of the positions. The laserbeam light source may be controlled to deflect a laserlight beam away from laserlight-sensitive regions, to reduce an intensity of a laserlight beam directed towards a laserlight-sensitive region, etc. Motion estimation may be used to generate the indications of positions corresponding to the laserlight-sensitive regions.
    Type: Application
    Filed: August 31, 2017
    Publication date: August 30, 2018
    Inventors: Danilo Pietro Pau, Emanuele PLEBANI
  • Patent number: 9986240
    Abstract: In an embodiment, digital video frames in a flow are subjected to a method of extraction of features including the operations of: extracting from the video frames respective sequences of pairs of keypoints/descriptors limiting to a threshold value the number of pairs extracted for each frame; sending the sequences extracted from an extractor module to a server for processing with a bitrate value variable in time; receiving the aforesaid bitrate value variable in time at the extractor as target bitrate for extraction; and limiting the number of pairs extracted by the extractor to a threshold value variable in time as a function of the target bitrate.
    Type: Grant
    Filed: December 30, 2016
    Date of Patent: May 29, 2018
    Assignee: STMicroelectronics S.r.l.
    Inventor: Danilo Pietro Pau