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CARE-DPP outperforms traditional methods by intelligently balancing uncertainty and novelty, leading to more effective biodiversity classification with less annotation effort.
Adaptive learning strategies can significantly enhance annotation efficiency in bioacoustic monitoring by intelligently balancing exploration and exploitation based on model confidence.
Forget general-purpose ecoacoustic models: task-oriented, region-specific training with DeepForestSound boosts detection performance to near-perfect AP scores (0.96+) for primates and elephants in African rainforests.
