NVIDIA Corporation
DEEP NEURAL NETWORK PROCESSING FOR SENSOR BLINDNESS DETECTION IN AUTONOMOUS MACHINE APPLICATIONS

Abstract:

In various examples, a deep neural network (DNN) is trained for sensor blindness detection using a region and context-based approach. Using sensor data, the DNN may compute locations of blindness or compromised visibility regions as well as associated blindness classifications and/or blindness attributes associated therewith. In addition, the DNN may predict a usability of each instance of the sensor data for performing one or more operations--such as operations associated with semi-autonomous or autonomous driving. The combination of the outputs of the DNN may be used to filter out instances of the sensor data--or to filter out portions of instances of the sensor data determined to be compromised--that may lead to inaccurate or ineffective results for the one or more operations of the system.