Patents by Inventor Carlo Eduardo Cabanero del Mundo
Carlo Eduardo Cabanero del Mundo 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: 20240119699Abstract: In one embodiment, a method includes receiving an input video comprising a plurality of image frames including an object of interest. Based on the plurality of image frames, a motion associated with the object of interest is determined, and the plurality of image frames are classified using a machine-learning model to identify one of the plurality of image frames that indicates a moment of perception of the determined motion.Type: ApplicationFiled: October 11, 2023Publication date: April 11, 2024Inventors: Hessam BAGHERINEZHAD, Carlo Eduardo Cabanero DEL MUNDO, Anish Jnyaneshwar PRABHU, Peter ZATLOUKAL, Lawrence Frederick ARNSTEIN
-
Patent number: 11816876Abstract: In one embodiment, a method includes receiving an input video comprising a plurality of image frames including an object of interest. Based on the plurality of image frames, a motion associated with the object of interest is determined, and the plurality of image frames are classified using a machine-learning model to identify one of the plurality of image frames that indicates detection of the determined motion.Type: GrantFiled: May 3, 2021Date of Patent: November 14, 2023Assignee: Apple Inc.Inventors: Hessam Bagherinezhad, Carlo Eduardo Cabanero Del Mundo, Anish Jnyaneshwar Prabhu, Peter Zatloukal, Lawrence Frederick Arnstein
-
Patent number: 11669585Abstract: In one embodiment, a method includes receiving an input tensor corresponding to a media object at a binary convolutional neural network, wherein the binary convolutional neural network comprises at least one binary convolution layer comprising one or more weights, and wherein the media object is associated with a particular task, binarizing the input tensor by the at least one binary convolution layer, binarizing the one or more weights by the at least one binary convolution layer, and generating an output corresponding to the particular task by the binary convolutional neural network based on the binarized input tensor and the binarized one or more weights.Type: GrantFiled: June 25, 2019Date of Patent: June 6, 2023Assignee: Apple Inc.Inventors: Carlo Eduardo Cabanero del Mundo, Ali Farhadi
-
Publication number: 20220222550Abstract: In one embodiment, a method includes providing, to a client system of a user, a user interface for display. The user interface may include a first set of options for selecting an artificial intelligence (AI) task for integrating into a user application, a second set of options for selecting one or more devices on which the user wants to deploy the selected AI task, and a third set of options for selecting one or more performance constraints specific to the selected devices. User specifications may be received based on user selections in the first, second, and third sets of options. A custom AI model may be generated based on the user specifications and sent to the client system of the user for integrating into the user application. The custom AI model once integrated may enable the user application to perform the selected AI task on the selected devices.Type: ApplicationFiled: January 24, 2022Publication date: July 14, 2022Inventors: Alexander James Oscar Craver KIRCHHOFF, Ali FARHADI, Anish Jnyaneshwar PRABHU, Carlo Eduardo Cabanero DEL MUNDO, Daniel Carl TORMOEN, Hessam BAGHERINEZHAD, Matthew S. WEAVER, Maxwell Christian HORTON, Mohammad RASTEGARI, Robert Stephen KARL, JR., Sophie LEBRECHT
-
Patent number: 11263540Abstract: In one embodiment, a method includes providing, to a client system of a user, a user interface for display. The user interface may include a first set of options for selecting an artificial intelligence (AI) task for integrating into a user application, a second set of options for selecting one or more devices on which the user wants to deploy the selected AI task, and a third set of options for selecting one or more performance constraints specific to the selected devices. User specifications may be received based on user selections in the first, second, and third sets of options. A custom AI model may be generated based on the user specifications and sent to the client system of the user for integrating into the user application. The custom AI model once integrated may enable the user application to perform the selected AI task on the selected devices.Type: GrantFiled: May 6, 2019Date of Patent: March 1, 2022Assignee: APPLE INC.Inventors: Alexander James Oscar Craver Kirchhoff, Ali Farhadi, Anish Jnyaneshwar Prabhu, Carlo Eduardo Cabanero del Mundo, Daniel Carl Tormoen, Hessam Bagherinezhad, Matthew S. Weaver, Maxwell Christian Horton, Mohammad Rastegari, Robert Stephen Karl, Jr., Sophie Lebrecht
-
Publication number: 20210272292Abstract: In one embodiment, a method includes receiving an input video comprising a plurality of image frames including an object of interest. Based on the plurality of image frames, a motion associated with the object of interest is determined, and the plurality of image frames are classified using a machine-learning model to identify one of the plurality of image frames that indicates detection of the determined motion.Type: ApplicationFiled: May 3, 2021Publication date: September 2, 2021Inventors: Hessam BAGHERINEZHAD, Carlo Eduardo Cabanero DEL MUNDO, Anish Jnyaneshwar PRABHU, Peter ZATLOUKAL, Lawrence Frederick ARNSTEIN
-
Patent number: 10997730Abstract: In one embodiment, a method includes receiving a machine-learning model trained to detect a specified motion using multiple videos, wherein each video has at least one frame labeled as a moment of perception of the specified motion, identifying an object-of-interest depicted in an input video, detecting a motion of the object-of-interest, determining that the detected motion is the specified motion, and classifying one of the frames of the input video as the moment of perception of the specified motion.Type: GrantFiled: August 21, 2019Date of Patent: May 4, 2021Assignee: Xnor.AI, Inc.Inventors: Hessam Bagherinezhad, Carlo Eduardo Cabanero del Mundo, Anish Jnyaneshwar Prabhu, Peter Zatloukal, Lawrence Frederick Arnstein
-
Publication number: 20210056709Abstract: In one embodiment, a method includes receiving a machine-learning model trained to detect a specified motion using multiple videos, wherein each video has at least one frame labeled as a moment of perception of the specified motion, identifying an object-of-interest depicted in an input video, detecting a motion of the object-of-interest, determining that the detected motion is the specified motion, and classifying one of the frames of the input video as the moment of perception of the specified motion.Type: ApplicationFiled: August 21, 2019Publication date: February 25, 2021Inventors: Hessam Bagherinezhad, Carlo Eduardo Cabanero del Mundo, Anish Jnyaneshwar Prabhu, Peter Zatloukal, Lawrence Frederick Arnstein
-
Publication number: 20200410318Abstract: In one embodiment, a method includes receiving an input tensor corresponding to a media object at a binary convolutional neural network, wherein the binary convolutional neural network comprises at least one binary convolution layer comprising one or more weights, and wherein the media object is associated with a particular task, binarizing the input tensor by the at least one binary convolution layer, binarizing the one or more weights by the at least one binary convolution layer, and generating an output corresponding to the particular task by the binary convolutional neural network based on the binarized input tensor and the binarized one or more weights.Type: ApplicationFiled: June 25, 2019Publication date: December 31, 2020Inventors: Carlo Eduardo Cabanero del Mundo, Ali Farhadi
-
Publication number: 20190340524Abstract: In one embodiment, a method includes providing, to a client system of a user, a user interface for display. The user interface may include a first set of options for selecting an artificial intelligence (AI) task for integrating into a user application, a second set of options for selecting one or more devices on which the user wants to deploy the selected AI task, and a third set of options for selecting one or more performance constraints specific to the selected devices. User specifications may be received based on user selections in the first, second, and third sets of options. A custom AI model may be generated based on the user specifications and sent to the client system of the user for integrating into the user application. The custom AI model once integrated may enable the user application to perform the selected AI task on the selected devices.Type: ApplicationFiled: May 6, 2019Publication date: November 7, 2019Inventors: Alexander James Oscar Craver Kirchhoff, Ali Farhadi, Anish Jnyaneshwar Prabhu, Carlo Eduardo Cabanero del Mundo, Daniel Carl Tormoen, Hessam Bagherinezhad, Matthew S. Weaver, Maxwell Christian Horton, Mohammad Rastegari, Robert Stephen Karl, JR., Sophie Lebrecht