SEABAD is a publicly released, balanced dataset of 50,000 curated 16 kHz audio clips spanning 1,677 tropical bird species, with a dual-branch curation pipeline and MobileNetV3-Small baseline reaching 99.57% accuracy.
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2 Pith papers cite this work. Polarity classification is still indexing.
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Semantic network analysis of reviews shows Eco fosters socio-political cognition of environmental issues while WolfQuest builds effective empathy via avatar vulnerability.
citing papers explorer
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SEABAD: A Tropical Bird Activity Detection Dataset for Passive Acoustic Monitoring
SEABAD is a publicly released, balanced dataset of 50,000 curated 16 kHz audio clips spanning 1,677 tropical bird species, with a dual-branch curation pipeline and MobileNetV3-Small baseline reaching 99.57% accuracy.
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Mapping Ecological Empathy: A Semantic Network Analysis of Player Perceptions in 3D Environmental Education Games
Semantic network analysis of reviews shows Eco fosters socio-political cognition of environmental issues while WolfQuest builds effective empathy via avatar vulnerability.