公开(公告)号：US20240362746A1

公开(公告)日：2024-10-31

申请号：US18770481

申请日：2024-07-11

Applicant: Google LLC

Inventor： Victor Carbune ,  Daniel M. Keysers ,  Thomas Deselaers

IPC: G06T3/4046 ,  G06T5/50

CPC classification number: G06T3/4046 ,  G06T5/50 ,  G06T2207/20081 ,  G06T2207/20084

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, that use generative adversarial models to increase the quality of sensor data generated by a first environmental sensor to resemble the quality of sensor data generated by another sensor having a higher quality than the first environmental sensor. A set of first and second training data generated by a first environmental sensor having a first quality and a second sensor having a target quality, respectively, is received. A generative adversarial mode is trained, using the set of first training data and the set of second training data, to modify sensor data from the first environmental sensor by reducing a difference in quality between the sensor data generated by the first environmental sensor and sensor data generated by the target environmental sensor.

公开(公告)号：US20240289926A1

公开(公告)日：2024-08-29

申请号：US18564915

申请日：2022-05-27

Applicant: Google LLC

Inventor： Carlos Riquelme Ruiz ,  André Susano Pinto ,  Basil Mustafa ,  Daniel M. Keysers ,  Joan Puigcerver i Perez ,  Maxim Neumann ,  Neil Matthew Tinmouth Houlsby ,  Rodolphe Jenatton

IPC: G06T5/60

CPC classification number: G06T5/60 ,  G06T2207/20084

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for generating predictions about images. One of the systems includes a neural network comprising a sequence of one or more network blocks that are each configured to perform operations comprising: obtaining a block input that represents an intermediate representation of an input image; determining a plurality of patches of the block input or of an updated representation of the block input, wherein each patch comprises a different subset of elements of the block input or of the updated representation of the block input; assigning each patch to one or more respective expert modules of a plurality of expert modules of the network block; for each patch of the plurality of patches, processing the patch using the corresponding expert modules to generate respective module outputs; and generating a block output by combining the module outputs.

公开(公告)号：US09965155B2

公开(公告)日：2018-05-08

申请号：US14671789

申请日：2015-03-27

Applicant: Google LLC

Inventor： Daniel M. Keysers ,  Thomas Deselaers ,  Victor Carbune

IPC: G06F3/0484 ,  H04W4/00 ,  H04L29/08 ,  G06F3/14 ,  G01S5/00 ,  G06F3/01 ,  G06F3/0481 ,  H04M1/725 ,  G06F3/0488

CPC classification number: G06F3/04842 ,  G01S5/0072 ,  G06F3/017 ,  G06F3/0481 ,  G06F3/04883 ,  G06F3/1423 ,  H04L67/18 ,  H04M1/7253 ,  H04M2250/16 ,  H04M2250/22 ,  H04W4/80

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for performing dynamic, stroke-based alignment of touch displays. In one aspect, a method include providing, for output by a first mobile computing device that (i) has a first proximity sensitive display and (ii) has been designated a primary display device, a primary alignment user interface. The methods also includes transmitting, by the first mobile computing device to a second mobile computing device that (i) has a second proximity sensitive display and (ii) has been designated a secondary display device, an instruction to output a secondary alignment user interface.