Automated monitoring of animal behaviour with barcodes and convolutional neural networks
Keyword(s):
AbstractBarcode-based tracking of individuals revolutionizes the study of animal behaviour, but further progress hinges on whether specific behaviours can be monitored. We achieve this goal by combining information obtained from the barcodes with image analysis through convolutional neural networks. Applying this novel approach to a challenging test case, the honeybee hive, we reveal that food exchange among bees generates two distinct social networks with qualitatively different transmission capabilities.
2019 ◽
Vol 7
(6)
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pp. 164-168
2021 ◽
2018 ◽
Vol 16
(12)
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pp. 814-827
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2019 ◽
Vol 8
(6S3)
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pp. 1385-1388
2017 ◽
Vol 2
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pp. 24-33
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2021 ◽
Vol 2089
(1)
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pp. 012013