Neural network applications in resource constrained environments

US10210451B2 · kind B2 · utility

Assignee

• Alpine Electronics of Silicon Valley, Inc. · US

Inventors

• Rocky Chau-Hsiung Lin · Cupertino, US
• Thomas Yamasaki · Villa Park, US
• Koichiro Kanda · San Jose, US
• Diego Rodriguez Risco · Campbell, US
• Alexander Joseph Ryan · Mountain View, US
• Samah Najeeb · Menlo Park, US
• Samir El Aouar · San Jose, US

Key dates

• Filing date: Apr 6, 2018
• Grant date: Feb 19, 2019
• Expiry date: Apr 6, 2038

Classification

• Technology area (CPC G): Physics
• CPC primary: G06N3/094
• WIPO field: Computer technology
• WIPO sector: Electrical engineering

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.