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This work proposes a latency-aware metric for multi-object tracking called streaming-HOTA (s-HOTA), and introduces an ultra-High-resolution Airborne Remote-sensing Dataset (HARD) annotated at three levels for object detection, multi-object tracking, and scene-level visual question answering.
Now you can adaptively control false discovery rates in your selections *after* seeing the data, letting you balance selection size and FDR based on observed evidence and downstream needs.
