4 papers
TRIM: Temporal Run-Time Monitoring of 3D Object Detection via Activation Statistics
Hakan Yekta Yatbaz, Konstantinos Koufos, Mehrdad Dianati
Reliable perception is essential to intelligent transportation systems, yet deep neural networks can silently miss safety-critical objects while continuing to produce apparently pl…
Integrity Monitoring of 3D Object Detection in Automated Driving Systems using Raw Activation Patterns and Spatial Filtering
Hakan Yekta Yatbaz, Mehrdad Dianati, Konstantinos Koufos +1
The deep neural network (DNN) models are widely used for object detection in automated driving systems (ADS). Yet, such models are prone to errors which can have serious safety imp…
Run-time Monitoring of 3D Object Detection in Automated Driving Systems Using Early Layer Neural Activation Patterns
Hakan Yekta Yatbaz, Mehrdad Dianati, Konstantinos Koufos +1
Monitoring the integrity of object detection for errors within the perception module of automated driving systems (ADS) is paramount for ensuring safety. Despite recent advancement…
Run-time Introspection of 2D Object Detection in Automated Driving Systems Using Learning Representations
Hakan Yekta Yatbaz, Mehrdad Dianati, Konstantinos Koufos +1
Reliable detection of various objects and road users in the surrounding environment is crucial for the safe operation of automated driving systems (ADS). Despite recent progresses…