Intersection pose detection

A system comprising:

• one or more central processing units (CPUs);
• one or more graphics processing units (GPUs);
• one or more hardware accelerators;
• and
• one or more sensors having one or more fields of view or one or more sensory fields, the one or more sensors to obtain sensor data,
• wherein the system is to:
• generate, using one or more neural networks and based at least on the sensor data, output data that classifies one or more first lanes of an intersection as including one or more entrances and one or more second lanes of the intersection as including one or more exits;
• generate, based at least on the output data, one or more proposed paths through the intersection;
• and
• cause, based at least on the one or more proposed paths, a machine to perform one or more planning, navigation, or control operations.

At least one system-on-a-chip (SoC), wherein individual SoCs of the at least one SoC comprises:

• one or more central processing units (CPUs);
• one or more graphics processing units (GPUs);
• one or more hardware accelerators;
• and
• wherein the at least one SoC is to cause a machine to navigate through an intersection based at least on a first classification indicating that a first lane is an entrance for the intersection and a second classification indicating that a second lane is an exit for the intersection, wherein the first classification and the second classification are determined based at least on one or more machine learning models processing sensor data obtained using one or more sensors of the machine.