Patents by Inventor Niels Brouwers

Niels Brouwers 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).

  • Generation of training data from a single image
    Patent number: 11741592
    Abstract: Techniques for anomaly detection are described. An exemplary method includes receiving a request to create a training data set from at least one image, the request to include an indication of the at least one image and at least one indication of an operation to perform on the at least one image to generate a plurality of images from the at least one image; creating a training dataset by extracting one or more chunks from a first at least one image according to the request; and receiving one or more requests to train an anomaly detection machine learning model using the created training dataset; and training an anomaly detection machine learning model according to one or more requests using the created training data.
    Type: Grant
    Filed: November 27, 2020
    Date of Patent: August 29, 2023
    Assignee: Amazon Technologies, Inc.
    Inventors: Joaquin Zepeda Salvatierra, Anant Patel, Shaun Ryan James McDowell, Prakash Krishnan, Ranju Das, Niels Brouwers, Barath Balasubramanian
  • ANOMALY DETECTION USING FEEDBACK TRAINING
    Publication number: 20220171995
    Abstract: Techniques for anomaly detection are described. An exemplary method includes receiving one or more requests to train an anomaly detection machine learning model using feedback-based training, the request to indicate one or more of a type of analysis to perform, a model selection indication, and a configuration for a training dataset; training the anomaly detection machine learning model according to the one or more requests using the training data; performing feedback-based training on the trained anomaly detection machine learning model; and using the retrained anomaly detection machine learning model.
    Type: Application
    Filed: November 27, 2020
    Publication date: June 2, 2022
    Inventors: Barath BALASUBRAMANIAN, Rahul BHOTIKA, Niels BROUWERS, Ranju DAS, Prakash KRISHNAN, Shaun Ryan James MCDOWELL, Anushri MAINTHIA, Rakesh Madhavan NAMBIAR, Anant PATEL, Avinash AGHORAM RAVICHANDRAN, Joaquin ZEPEDA SALVATIERRA, Gurumurthy SWAMINATHAN
  • FEEDBACK-BASED TRAINING FOR ANOMALY DETECTION
    Publication number: 20220172100
    Abstract: Techniques for feedback-based training are described.
    Type: Application
    Filed: November 27, 2020
    Publication date: June 2, 2022
    Inventors: Barath BALASUBRAMANIAN, Rahul BHOTIKA, Niels BROUWERS, Ranju DAS, Prakash KRISHNAN, Shaun Ryan James MCDOWELL, Anushri MAINTHIA, Rakesh Madhavan NAMBIAR, Anant PATEL, Avinash AGHORAM RAVICHANDRAN, Joaquin ZEPEDA SALVATIERRA, Gurumurthy SWAMINATHAN
  • GENERATION OF TRAINING DATA FROM A SINGLE IMAGE
    Publication number: 20220172342
    Abstract: Techniques for anomaly detection are described. An exemplary method includes receiving a request to create a training data set from at least one image, the request to include an indication of the at least one image and at least one indication of an operation to perform on the at least one image to generate a plurality of images from the at least one image; creating a training dataset by extracting one or more chunks from a first at least one image according to the request; and receiving one or more requests to train an anomaly detection machine learning model using the created training dataset; and training an anomaly detection machine learning model according to one or more requests using the created training data.
    Type: Application
    Filed: November 27, 2020
    Publication date: June 2, 2022
    Inventors: Joaquin ZEPEDA SALVATIERRA, Anant PATEL, Shaun Ryan James MCDOWELL, Prakash KRISHNAN, Ranju DAS, Niels BROUWERS, Barath BALASUBRAMANIAN
  • Application testing and analysis
    Patent number: 9009677
    Abstract: Application testing and analysis may include performing perturbations to affect an environment associated with the application executing on a user device without affecting other applications executing on the user device. The execution of the application may be traced while the perturbations are being performed to determine an amount of resources of the user device consumed by the application and to determine whether a performance of the application was degraded.
    Type: Grant
    Filed: March 18, 2013
    Date of Patent: April 14, 2015
    Assignee: Microsoft Technology Licensing, LLC
    Inventors: Feng Zhao, Niels Brouwers, Nicholas Donald Atkins Lane, Chieh-Jan Mike Liang, Ranveer Chandra
  • APPLICATION TESTING AND ANALYSIS
    Publication number: 20140282425
    Abstract: Application testing and analysis may include performing perturbations to affect an environment associated with the application executing on a user device without affecting other applications executing on the user device. The execution of the application may be traced while the perturbations are being performed to determine an amount of resources of the user device consumed by the application and to determine whether a performance of the application was degraded.
    Type: Application
    Filed: March 18, 2013
    Publication date: September 18, 2014
    Applicant: MICROSOFT CORPORATION
    Inventors: Feng Zhao, Niels Brouwers, Nicholas Donald Atkins Lane, Chieh-Jan Mike Liang, Ranveer Chandra