Patents by Inventor Maxwell Donald Emmet Collins

Maxwell Donald Emmet Collins 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).

  • Neural architecture search for dense image prediction tasks
    Patent number: 10853726
    Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for determining neural network architectures. One of the methods includes obtaining training data for a dense image prediction task; and determining an architecture for a neural network configured to perform the dense image prediction task, comprising: searching a space of candidate architectures to identify one or more best performing architectures using the training data, wherein each candidate architecture in the space of candidate architectures comprises (i) the same first neural network backbone that is configured to receive an input image and to process the input image to generate a plurality of feature maps and (ii) a different dense prediction cell configured to process the plurality of feature maps and to generate an output for the dense image prediction task; and determining the architecture for the neural network based on the best performing candidate architectures.
    Type: Grant
    Filed: May 29, 2019
    Date of Patent: December 1, 2020
    Assignee: Google LLC
    Inventors: Barret Zoph, Jonathon Shlens, Yukun Zhu, Maxwell Donald Emmet Collins, Liang-Chieh Chen, Gerhard Florian Schroff, Hartwig Adam, Georgios Papandreou
  • NEURAL ARCHITECTURE SEARCH FOR DENSE IMAGE PREDICTION TASKS
    Publication number: 20190370648
    Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for determining neural network architectures. One of the methods includes obtaining training data for a dense image prediction task; and determining an architecture for a neural network configured to perform the dense image prediction task, comprising: searching a space of candidate architectures to identify one or more best performing architectures using the training data, wherein each candidate architecture in the space of candidate architectures comprises (i) the same first neural network backbone that is configured to receive an input image and to process the input image to generate a plurality of feature maps and (ii) a different dense prediction cell configured to process the plurality of feature maps and to generate an output for the dense image prediction task; and determining the architecture for the neural network based on the best performing candidate architectures.
    Type: Application
    Filed: May 29, 2019
    Publication date: December 5, 2019
    Inventors: Barret Zoph, Jonathon Shlens, Yukun Zhu, Maxwell Donald Emmet Collins, Liang-Chieh Chen, Gerhard Florian Schroff, Hartwig Adam, Georgios Papandreou