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Skip to Search Results- 1Applegate, Kelly
- 1Bayne, Erin
- 1Boyce, M. S.
- 1Bulitko, Vadim
- 1Campbell, Kimberley A.
- 1Congdon, Jenna V.
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2017-04-05
McMillan, Neil, Hahn, Allison H., Congdon, Jenna V., Campbell, Kimberley A., Hoang, J., Scully, Erin N., Spetch, Marcia L., Sturdy, Christopher B.
Chickadees are high-metabolism, non-migratory birds, and thus an especially interesting model for studying how animals follow patterns of food availability over time. Here, we studied whether black-capped chickadees (Poecile atricapillus) could learn to reverse their behavior and/or to anticipate...
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Pre-processing spectrogram parameters improve the accuracy of bioacoustic classification using convolutional neural networks
Download2021-06-01
Knight, Elly C., Hernandez, Sergio Poo, Bayne, Erin, Bulitko, Vadim, Tucker, Benjamin V.
A variety of automated classification approaches have been developed to extract species detection information from large bioacoustic datasets. Convolutional neural networks (CNNs) are an image classification technique that can be operated on the spectrogram of an audio recording. Using CNNs for...
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The influence of morphological variation on migration performance in a trans-hemispheric migratory songbird
Download2015-01-01
Lam, Lawrence, McKinnon, Emily A., Ray, James D., Pearman, Myrna, Hvenegaard, Glen T., Mejeur, James, Moscar, Lauren, Pearson, Mackenzie, Applegate, Kelly, Mammenga, Paul, Tautin, John, Fraser, Kevin C.
For long-distance migratory songbirds, morphological traits such as longer wings and a smaller body size are predicted to increase migration efficiency. Due to previous limitations in our ability to track the long-distance journeys of small-bodied birds, the relationship between morphology and...