5 papers
FSNet: A Failure Detection Framework for Semantic Segmentation
Quazi Marufur Rahman, Niko Sünderhauf, Peter Corke +1
Semantic segmentation is an important task that helps autonomous vehicles understand their surroundings and navigate safely. During deployment, even the most mature segmentation mo…
Run-Time Monitoring of Machine Learning for Robotic Perception: A Survey of Emerging Trends
Quazi Marufur Rahman, Peter Corke, Feras Dayoub
As deep learning continues to dominate all state-of-the-art computer vision tasks, it is increasingly becoming an essential building block for robotic perception. This raises impor…
Online Monitoring of Object Detection Performance During Deployment
Quazi Marufur Rahman, Niko Sünderhauf, Feras Dayoub
During deployment, an object detector is expected to operate at a similar performance level reported on its testing dataset. However, when deployed onboard mobile robots that opera…
Per-frame mAP Prediction for Continuous Performance Monitoring of Object Detection During Deployment
Quazi Marufur Rahman, Niko Sünderhauf, Feras Dayoub
Performance monitoring of object detection is crucial for safety-critical applications such as autonomous vehicles that operate under varying and complex environmental conditions.…
Did You Miss the Sign? A False Negative Alarm System for Traffic Sign Detectors
Quazi Marufur Rahman, Niko Sünderhauf, Feras Dayoub
Object detection is an integral part of an autonomous vehicle for its safety-critical and navigational purposes. Traffic signs as objects play a vital role in guiding such systems.…