Diego R Risco

US Patent:

20230023870, Jan 26, 2023

Filed:

Oct 3, 2022

Appl. No.:

17/937772

Inventors:

- Santa Clara CA, US
Thomas Yamasaki - Anaheim Hills CA, US
Koichiro Kanda - San Jose CA, US
Diego Rodriguez Risco - Campbell CA, US
Alexander Joseph Ryan - Mountain View CA, US
Samah Najeeb - Menlo Park CA, US
Samir El Aouar - San Jose CA, US

International Classification:

G06N 3/08
G06N 3/063
G06N 3/04

Abstract:

Systems and methods are disclosed for applying neural networks in resource-constrained environments. A system may include a sensor located in a resource-constrained environment configured to generate first sensor data and second sensor data of the resource-constrained environment. The system may also include a first computing device not located in the resource-constrained environment configured to produce a neural network structure based on the first sensor data. The system may also include a second computing device configured to determine a state of the resource-constrained environment based on input of the second sensor data to the neural network structure. The system may also include a controller located in the resource-constrained environment configured to control a device in the resource-constrained environment based on the state of the resource-constrained environment determined by the second computing device. The second computing device may be further configured to calculate an activation area for the neural network structure.

US Patent:

20190325219, Oct 24, 2019

Filed:

Apr 19, 2019

Appl. No.:

16/389779

Inventors:

- Santa Clara CA, US
Thomas Yamasaki - Anaheim Hills CA, US
Koichiro Kanda - San Jose CA, US
Diego Rodriguez Risco - Campbell CA, US
Alexander Joseph Ryan - Mountain View CA, US
Samah Najeeb - Menlo Park CA, US
Samir El Aouar - San Jose CA, US

International Classification:

G06K 9/00

Abstract:

Devices, systems and processes for an integrated internal and external camera system that enhances the passenger experience in vehicles are described. One example method for enhancing a passenger experiences includes capturing a first set of images of an area around the vehicle using an external camera system, capturing a second set of images of one or more passengers inside the vehicle using an internal camera system, recognizing at least one gesture made by the one or more passengers based on the second set of images, identifying an object or a location external to the vehicle based on the first set of images and the at least one gesture, and displaying information related to the object or the location to the one or more passengers.

US Patent:

20190171937, Jun 6, 2019

Filed:

Feb 4, 2019

Appl. No.:

16/267285

Inventors:

- Santa Clara CA, US
Thomas Yamasaki - Anaheim Hills CA, US
Koichiro Kanda - San Jose CA, US
Diego Rodriguez Risco - Campbell CA, US
Alexander Joseph Ryan - Mountain View CA, US

International Classification:

G06N 3/08
G06N 3/063
G06N 3/04

Abstract:

Systems and methods are disclosed for applying neural networks in resource-constrained environments. A system may include a sensor located in a resource-constrained environment configured to generate sensor data of the resource-constrained environment. The system may also include a first computing device not located in the resource-constrained environment configured to produce a neural network structure based on the sensor data. The system may further include a second computing device located in the resource-constrained environment configured to provide the sensor data as input to the neural network structure. The second computing device may be further configured to determine a state of the resource-constrained environment based on the input of the sensor data to the neural network structure.

US Patent:

20190171938, Jun 6, 2019

Filed:

Feb 4, 2019

Appl. No.:

16/267317

Inventors:

- Santa Clara CA, US
Thomas Yamasaki - Anaheim Hills CA, US
Koichiro Kanda - San Jose CA, US
Diego Rodriguez Risco - Campbell CA, US
Alexander Joseph Ryan - Mountain View CA, US
Samah Najeeb - Menlo Park CA, US
Samir El Aouar - San Jose CA, US

International Classification:

G06N 3/08
G06N 3/063
G06N 3/04

Abstract:

Systems and methods are disclosed for applying neural networks in resource-constrained environments. A system may include a sensor located in a resource-constrained environment configured to generate first sensor data and second sensor data of the resource-constrained environment. The system may also include a first computing device not located in the resource-constrained environment configured to produce a neural network structure based on the first sensor data. The system may also include a second computing device configured to determine a state of the resource-constrained environment based on input of the second sensor data to the neural network structure. The system may also include a controller located in the resource-constrained environment configured to control a device in the resource-constrained environment based on the state of the resource-constrained environment determined by the second computing device. The second computing device may be further configured to calculate an activation area for the neural network structure.

US Patent:

20180232638, Aug 16, 2018

Filed:

Apr 5, 2018

Appl. No.:

15/946678

Inventors:

- Santa Clara CA, US
Thomas Yamasaki - Anaheim Hills CA, US
Koichiro Kanda - San Jose CA, US
Diego Rodriguez Risco - Campbell CA, US
Alexander Joseph Ryan - Mountain View CA, US

International Classification:

G06N 3/08
G06N 3/04
G06N 3/063

Abstract:

Systems and methods are disclosed for applying neural networks in resource-constrained environments. A system may include a sensor located in a resource-constrained environment configured to generate sensor data of the resource-constrained environment. The system may also include a first computing device not located in the resource-constrained environment configured to produce a neural network structure based on the sensor data. The system may further include a second computing device located in the resource-constrained environment configured to provide the sensor data as input to the neural network structure. The second computing device may be further configured to determine a state of the resource-constrained environment based on the input of the sensor data to the neural network structure.

US Patent:

20180232639, Aug 16, 2018

Filed:

Apr 6, 2018

Appl. No.:

15/947295

Inventors:

- Santa Clara CA, US
Thomas Yamasaki - Anaheim Hills CA, US
Koichiro Kanda - San Jose CA, US
Diego Rodriguez Risco - Campbell CA, US
Alexander Joseph Ryan - Mountain View CA, US
Samah Najeeb - Menlo Park CA, US
Samir El Aouar - San Jose CA, US

International Classification:

G06N 3/08
G06N 3/063
G06N 3/04

Abstract:

Systems and methods are disclosed for applying neural networks in resource-constrained environments. A system may include a sensor located in a resource-constrained environment configured to generate first sensor data and second sensor data of the resource-constrained environment. The system may also include a first computing device not located in the resource-constrained environment configured to produce a neural network structure based on the first sensor data. The system may also include a second computing device configured to determine a state of the resource-constrained environment based on input of the second sensor data to the neural network structure. The system may also include a controller located in the resource-constrained environment configured to control a device in the resource-constrained environment based on the state of the resource-constrained environment determined by the second computing device. The second computing device may be further configured to calculate an activation area for the neural network structure.

US Patent:

20180025272, Jan 25, 2018

Filed:

Sep 8, 2017

Appl. No.:

15/699298

Inventors:

- Santa Clara CA, US
Thomas Yamasaki - Anaheim Hills CA, US
Koichiro Kanda - San Jose CA, US
Diego Rodriguez Risco - Campbell CA, US
Alexander Joseph Ryan - Mountain View CA, US

International Classification:

G06N 3/08
G06N 3/04

Abstract:

Systems and methods are disclosed for applying neural networks in resource-constrained environments. A system may include a sensor located in a resource-constrained environment configured to generate sensor data of the resource-constrained environment. The system may also include a first computing device not located in the resource-constrained environment configured to produce a neural network structure based on the sensor data. The system may further include a second computing device located in the resource-constrained environment configured to provide the sensor data as input to the neural network structure. The second computing device may be further configured to determine a state of the resource-constrained environment based on the input of the sensor data to the neural network structure.