Occlusion and uncertainty sensitive model training for vehicle applications

Abstract

This disclosure provides systems, methods, and devices for machine learning techniques for improved training, such as for vehicle surroundings analysis. In one aspect, a method is provided that includes receiving image data and position data from the area surrounding a vehicle, determining initial feature data based on the received data, and determining updated feature data for training a first model. The updated feature data may be determined based on uncertainty measures for portions of the initial feature data, occluded regions within the initial feature data, or combinations thereof. In certain aspects, the first model may be trained using knowledge distillation techniques. Other aspects and features are also claimed and described.