Participation in MUSEKDE 2026 (IEEE MDM 2026)
Our lab member and PhD candidate Grigorios Papanikolaou presented Trajectory-Aware Adaptive Inference in Object Detection Models at the 1st Workshop on Multi-Sensor Trajectory Knowledge Discovery and Extraction (MUSEKDE 2026), co-located with the 27th IEEE International Conference on Mobile Data Management (MDM 2026, Athens). The study presents a trajectory-aware approach to real-time maritime perception by integrating GPS trajectory data into a YOLOv8-based object detection framework. The proposed method employs an early-exit mechanism that evaluates inter-vessel speed and distance to dynamically adapt computational effort, enabling faster processing of low-risk scenarios while reserving the full model for high-risk, close-proximity situations, thereby achieving an effective balance between accuracy and efficiency. https://arxiv.org/abs/2605.16397