Patents by Inventor Rakesh Madhavan Nambiar

Rakesh Madhavan Nambiar 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).

  • Patent number: 10380461
    Abstract: Approaches introduce a pre-processing and post-processing framework to a neural network-based approach to identify items represented in an image. For example, a classifier that is trained on several categories can be provided. An image that includes a representation of an item of interest is obtained. Rotated versions of the image are generated and each of a subset of the rotated images is analyzed to determine a probability that a respective image includes an instance of a particular category. The probabilities can be used to determine a probability distribution of output category data, and the data can be analyzed to select an image of the rotated versions of the image. Thereafter, a categorization tree can then be utilized, whereby for the item of interest represented the image, the category of the item can be determined. The determined category can be provided to an item retrieval algorithm to determine primary content for the item of interest.
    Type: Grant
    Filed: October 20, 2017
    Date of Patent: August 13, 2019
    Assignee: A9.COM, INC.
    Inventors: Avinash Aghoram Ravichandran, Matias Omar Gregorio Benitez, Rahul Bhotika, Scott Daniel Helmer, Anshul Kumar Jain, Junxiong Jia, Rakesh Madhavan Nambiar, Oleg Rybakov
  • Patent number: 9830534
    Abstract: Approaches introduce a pre-processing and post-processing framework to a neural network-based approach to identify items represented in an image. For example, a classifier that is trained on several categories can be provided. An image that includes a representation of an item of interest is obtained. Rotated versions of the image are generated and each of a subset of the rotated images is analyzed to determine a probability that a respective image includes an instance of a particular category. The probabilities can be used to determine a probability distribution of output category data, and the data can be analyzed to select an image of the rotated versions of the image. Thereafter, a categorization tree can then be utilized, whereby for the item of interest represented the image, the category of the item can be determined. The determined category can be provided to an item retrieval algorithm to determine primary content for the item of interest.
    Type: Grant
    Filed: December 16, 2015
    Date of Patent: November 28, 2017
    Assignee: A9.com, Inc.
    Inventors: Avinash Aghoram Ravichandran, Matias Omar Gregorio Benitez, Rahul Bhotika, Scott Daniel Helmer, Anshul Kumar Jain, Junxiong Jia, Rakesh Madhavan Nambiar, Oleg Rybakov
  • Patent number: 9305227
    Abstract: Embodiments of the subject technology provide for a hybrid OCR approach which combines server and device side processing that can offset disadvantages of performing OCR solely on the server side or the device side. More specifically, the subject technology utilizes image characteristics such as glyph details and image quality measurements to opportunistically schedule OCR processing on the mobile device and/or server. In this regard, text extracted by a “faster” OCR engine (e.g., one with less latency) is displayed to a user, which is then updated by the result of a more accurate OCR engine (e.g., an OCR engine provided by the server). This approach allows factoring in additional parameters such as network latency and user preference for making scheduling decisions. Thus, the subject technology may provide significant gains in terms of reduced latency and increased accuracy by implementing one or more techniques associated with this hybrid OCR approach.
    Type: Grant
    Filed: December 23, 2013
    Date of Patent: April 5, 2016
    Assignee: Amazon Technologies, Inc.
    Inventors: Rakesh Madhavan Nambiar, Sonjeev Jahagirdar, Matthew Joseph Cole, Matias Omar Gregorio Benitez, Junxiong Jia, David Paul Ramos
  • Patent number: 8965117
    Abstract: Embodiments of the subject technology provide methods and systems of image pre-processing for improving the accuracy of optical character recognition (OCR) and reducing the power consumption on a given computing device (e.g., mobile computing device). The subject technology, in some examples, classifies an image received from a camera of a mobile computing device into one or more classes: 1) normal background, 2) textured background, 3) image with text, 4) image with barcode, 5) image with QR code, and/or 6) image with clutter or “garbage.” Based on the classes associated with the image, the subject technology may forgo certain image processing operations, when the image is not associated with a particular class, in order to save resources (e.g., CPU cycles, battery power, memory usage, etc.) on the mobile computing device.
    Type: Grant
    Filed: December 17, 2013
    Date of Patent: February 24, 2015
    Assignee: Amazon Technologies, Inc.
    Inventors: Oleg Rybakov, Christopher John Lish, Chang Yuan, Junxiong Jia, Rakesh Madhavan Nambiar, Matias Omar Gregorio Benitez