4 papers
From Model Uncertainty to Human Attention: Localization-Aware Visual Cues for Scalable Annotation Review
Moussa Kassem Sbeyti, Joshua Holstein, Philipp Spitzer +2
High-quality labeled data is essential for training robust machine learning models, yet obtaining annotations at scale remains expensive. AI-assisted annotation has therefore becom…
Probabilistic Object Detection with Conformal Prediction
Christopher Ries, Moussa Kassem Sbeyti, Nicolas Bianco +1
Conformal Prediction (CP) is a distribution-free method for constructing prediction sets with marginal finite-sample coverage guarantees, making it a suitable framework for reliabl…
Depth as Prior Knowledge for Object Detection
Moussa Kassem Sbeyti, Nadja Klein
Detecting small and distant objects remains challenging for object detectors due to scale variation, low resolution, and background clutter. Safety-critical applications require re…
Streamlining the Development of Active Learning Methods in Real-World Object Detection
Moussa Kassem Sbeyti, Nadja Klein, Michelle Karg +2
Active learning (AL) for real-world object detection faces computational and reliability challenges that limit practical deployment. Developing new AL methods requires training mul…