A black-box active learning method selects 30% of camera-trap data and outperforms full-data training on the SAWIT benchmark in a single-run evaluation.
Dataset We validated our method on SAWIT [18], a benchmark dataset of small-sized animals captured from camera traps in the wild
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A model-agnostic active learning approach for animal detection from camera traps
A black-box active learning method selects 30% of camera-trap data and outperforms full-data training on the SAWIT benchmark in a single-run evaluation.