3 papers
cs.LG2025
Logit Scaling for Out-of-Distribution Detection
Andrija Djurisic, Rosanne Liu, Mladen Nikolic
The safe deployment of machine learning and AI models in open-world settings hinges critically on the ability to detect out-of-distribution (OOD) data accurately, data samples that…
cs.CV2024
Engineering an Efficient Object Tracker for Non-Linear Motion
Momir AdžemoviÄ, Predrag TadiÄ, Andrija PetroviÄ +1
The goal of multi-object tracking is to detect and track all objects in a scene while maintaining unique identifiers for each, by associating their bounding boxes across video fram…
cs.CV2024
Beyond Kalman Filters: Deep Learning-Based Filters for Improved Object Tracking
Momir AdžemoviÄ, Predrag TadiÄ, Andrija PetroviÄ +1
Traditional tracking-by-detection systems typically employ Kalman filters (KF) for state estimation. However, the KF requires domain-specific design choices and it is ill-suited to…