Nicholas A Johnston

US Patent:

20200311548, Oct 1, 2020

Filed:

Oct 29, 2019

Appl. No.:

16/666689

Inventors:

- Mountain View CA, US
Saurabh Singh - Mountain View CA, US
Johannes Balle - San Francisco CA, US
Sami Ahmad Abu-El-Haija - East Palo Alto CA, US
Nicholas Johnston - San Jose CA, US
George Dan Toderici - Mountain View CA, US

International Classification:

G06N 3/08
G06N 3/063
G06K 9/62
G06F 17/15

Abstract:

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for receiving, by a neural network (NN), a dataset for generating features from the dataset. A first set of features is computed from the dataset using at least a feature layer of the NN. The first set of features i) is characterized by a measure of informativeness; and ii) is computed such that a size of the first set of features is compressible into a second set of features that is smaller in size than the first set of features and that has a same measure of informativeness as the measure of informativeness of the first set of features. The second set of features if generated from the first set of features using a compression method that compresses the first set of features to generate the second set of features.

US Patent:

20200111238, Apr 9, 2020

Filed:

May 29, 2018

Appl. No.:

16/617484

Inventors:

- Mountain View CA, US
Damien Vincent - Zurich, CH
David Charles Minnen - Mountain View CA, US
Saurabh Singh - Mountain View CA, US
Sung Jin Hwang - Mountain View CA, US
Nicholas Johnston - San Jose CA, US
Joel Eric Shor - Mountain View CA, US
George Dan Toderici - Mountain View CA, US

International Classification:

G06T 9/00
G06T 3/40
G06T 7/00
G06N 3/04
G06N 3/08

Abstract:

Methods, systems, and apparatus, including computer programs encoded on computer storage media, for image compression and reconstruction. An image encoder system receives a request to generate an encoded representation of an input image that has been partitioned into a plurality of tiles and generates the encoded representation of the input image. To generate the encoded representation, the system processes a context for each tile using a spatial context prediction neural network that has been trained to process context for an input tile and generate an output tile that is a prediction of the input tile. The system determines a residual image between the particular tile and the output tile generated by the spatial context prediction neural network by process the context for the particular tile and generates a set of binary codes for the particular tile by encoding the residual image using an encoder neural network.

US Patent:

20200027247, Jan 23, 2020

Filed:

Jul 18, 2019

Appl. No.:

16/515586

Inventors:

- Mountain View CA, US
Saurabh Singh - Mountain View CA, US
Johannes Balle - San Francisco CA, US
Troy Chinen - Newark CA, US
Sung Jin Hwang - Mountain View CA, US
Nicholas Johnston - San Jose CA, US
George Dan Toderici - Mountain View CA, US

International Classification:

G06T 9/00
G06T 3/40
G06N 3/08
G06N 20/00
G06F 17/18

Abstract:

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for compressing and decompressing data. In one aspect, a method comprises: processing data using an encoder neural network to generate a latent representation of the data; processing the latent representation of the data using a hyper-encoder neural network to generate a latent representation of an entropy model; generating an entropy encoded representation of the latent representation of the entropy model; generating an entropy encoded representation of the latent representation of the data using the latent representation of the entropy model; and determining a compressed representation of the data from the entropy encoded representations of: (i) the latent representation of the data and (ii) the latent representation of the entropy model used to entropy encode the latent representation of the data.

US Patent:

20190356931, Nov 21, 2019

Filed:

May 16, 2019

Appl. No.:

16/413992

Inventors:

- Mountain View CA, US
Michele Covell - Woodside CA, US
Shumeet Baluja - La Jolla CA, US
Nicholas Milo Johnston - San Jose CA, US
Pascal Massimino - Orsay, FR

International Classification:

H04N 19/90
H04N 19/186
H04N 19/176
G06T 9/00

Abstract:

An encoder system can include a pixel grid generator to receive an image having a first dimension, generate a grid having a second dimension, add a plurality of points to positions on the grid, and map a plurality of pixels of the image to the plurality of points. The encoder system can include a color module to assign a color to each of the plurality of points using a color table, a triangulation module to generate a plurality of vertices based on the plurality of points and triangulate the grid using the vertices, and a compression module to compress the vertices as a set of compressed vertex positions and a set of vertex colors.

US Patent:

20150170664, Jun 18, 2015

Filed:

Mar 14, 2013

Appl. No.:

13/803497

Inventors:

Ryan P. DOHERTY - Mountain View CA, US
Nicholas M. JOHNSTON - Mountain View CA, US

Assignee:

Google Inc. - Mountain View CA

International Classification:

G10L 21/00

Abstract:

A device may receive, from a peripheral device, information for controlling the peripheral device. The information for controlling the peripheral device may include information identifying a voice command associated with the peripheral device and information identifying a function corresponding to the voice command. The device may receive, from a user, the voice command. The device may cause the peripheral device to perform the function based on receiving the voice command.