Hierarchical machine-learning network architecture

Patent metadata

Field	Value
Publication number	US-2021216793-A1
Application number	US-202117215938-A
Country	US
Kind code	A1
Filing date	Mar 29, 2021
Priority date	Jan 2, 2019
Publication date	Jul 15, 2021
Grant date	—

Abstract

The techniques discussed herein may comprise refining a classification of an object detected as being represented in sensor data. For example, refining the classification may comprise determining a sub-classification of the object.

First claim

What is claimed is:

1 . A method comprising:
receiving, from a sensor of an autonomous vehicle, an image; providing, as input to a first neural network, the image; receiving, from the first neural network, a feature map, a region of interest, a classification, and a first probability associated with an object represented in the image; providing, as input to a second neural network, at least a portion of the feature map that corresponds to the region of interest; receiving, from the second neural network, a sub-classification and a second probability associated therewith; and controlling operation of the autonomous vehicle based at least in part on at least one of the classification or the sub-classification.

Assignees

• Zoox Inc

Inventors

• Goel Kratarth
• Tariq Sarah

Classifications

• G06V10/255

  Detecting or recognising potential candidate objects based on visual cues, e.g. shapes · CPC title

• G06V10/82 Primary

  using neural networks · CPC title

• G06V20/58

  Recognition of moving objects or obstacles, e.g. vehicles or pedestrians; Recognition of traffic objects, e.g. traffic signs, traffic lights or roads · CPC title

• G06F18/24

  Classification techniques · CPC title

• G06N3/09

  Supervised learning · CPC title