15 lines
938 B
Markdown
15 lines
938 B
Markdown
---
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layout: single
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title: "Primate Vocalization Classification"
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categories: research audio deep-learning anomalie-detection
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excerpt: "A Deep and Recurrent Architecture"
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header:
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teaser: assets/figures/11_recurrent_primate_workflow.jpg
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---
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{:style="display:block; width:40%" .align-right}
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This study introduces a deep, recurrent architecture for classifying primate vocalizations, leveraging bidirectional Long Short-Term Memory networks and advanced techniques like normalized softmax and focal loss. Bayesian optimization was used to fine-tune hyperparameters, and the model was evaluated on a dataset of primate calls from an African sanctuary, showcasing the effectiveness of acoustic monitoring in wildlife conservation efforts.
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{% cite muller2021deep %}
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{:style="display:block; width:85%" .align-center} |