YOLO Meets Mixture-of-Experts: Adaptive Expert Routing for Robust Object Detection

This paper presents a novel Mixture-of-Experts framework for object detection, incorporating adaptive routing among multiple YOLOv9-T experts to enable dynamic feature specialization and achieve higher mean Average Precision (mAP) and Average Recall (AR) compared to a single YOLOv9-T model.

Find the Leak, Fix the Split: Cluster-Based Method to Prevent Leakage in Video-Derived Datasets

We propose a cluster-based frame selection strategy to mitigate information leakage in video-derived frames datasets. By grouping visually similar frames before splitting into training, validation, and test sets, the method produces more representative, balanced, and reliable dataset partitions.