most citedAutomated detection of gibbon calls from passive acoustic monitoring data using convolutional neural networks in the "torch for R" ecosystem

1 citations · 1 across the 1 of their papers we have counts for

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2 papers

q-bio.QM2024★ 1 cited

Automated detection of gibbon calls from passive acoustic monitoring data using convolutional neural networks in the "torch for R" ecosystem

Dena J. Clink, Jinsung Kim, Hope Cross-Jaya +9

Automated detection of acoustic signals is crucial for effective monitoring of sound-producing animals and their habitats across ecologically relevant spatial and temporal scales.…

eess.AS2019

GIBBONFINDR: An R package for the detection and classification of acoustic signals

Dena J. Clink, Holger Klinck

The recent improvements in recording technology, data storage and battery life have led to an increased interest in the use of passive acoustic monitoring for a variety of research…